{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\replication_all.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}29 May 2024, 15:49:34

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\Table1.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/Table1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/Table1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\Table1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations{c )-}\label{c -(}tab:donations{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: regress `x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 rdrobust `x' margin_victory ,  p(1) vce(cluster muni_code)
{txt}  7{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  9{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt} 10{com}.                 local N_`x' = `e(N)'
{txt} 11{com}.                 local poly_`x' = `e(p)'
{txt} 12{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 13{com}.                 local beta2_`x' : di %5.3f `e(tau_bc)'
{txt} 14{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 15{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 16{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 17{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 18{com}.                         
.                 *P-values
.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 19{com}.                 scalar pval2_`x' = e(pv_rb)
{txt} 20{com}.                 
.                 
.                 regress `x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 21{com}. 
.                 local N_`x' : di %5.0f e(N)
{txt} 22{com}.                 local R2_`x' : di %5.3f e(r2)
{txt} 23{com}. 
.                 matrix b = e(b)
{txt} 24{com}.                 matrix v = e(V)
{txt} 25{com}.                 matrix res=r(table)
{txt} 26{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 27{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 28{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 29{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 30{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 31{com}.         
. 
.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      327{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      413{col 34}      492

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13972{col 33} .03956{col 43}-3.5318{col 52}0.000{col 60}-.217256{col 73}-.062182
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.4091{col 52}0.001{col 60}-.241036{col 73}-.065058
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,150
                                                {txt}F(3, 792)         =  {res}    11.09
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0316
                                                {txt}Root MSE          =    {res} .21794

{txt}{ralign 86:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}        donate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0950474{col 34}{space 2} .0221724{col 45}{space 1}   -4.29{col 54}{space 3}0.000{col 62}{space 4} -.138571{col 75}{space 3}-.0515238
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.0756904{col 34}{space 2} .1856415{col 45}{space 1}   -0.41{col 54}{space 3}0.684{col 62}{space 4}-.4400978{col 75}{space 3} .2887171
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1453867{col 34}{space 2} .1681351{col 45}{space 1}    0.86{col 54}{space 3}0.387{col 62}{space 4}-.1846565{col 75}{space 3} .4754298
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1523377{col 34}{space 2} .0192309{col 45}{space 1}    7.92{col 54}{space 3}0.000{col 62}{space 4} .1145881{col 75}{space 3} .1900873
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      306{col 34}      357{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      443{col 34}      520

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11359{col 33} .03363{col 43}-3.3771{col 52}0.001{col 60}-.179511{col 73}-.047665
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.2711{col 52}0.001{col 60}-.200497{col 73}-.050253
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,150
                                                {txt}F(3, 792)         =  {res}     8.55
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0252
                                                {txt}Root MSE          =    {res} .18762

{txt}{ralign 86:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                  b5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0772252{col 34}{space 2} .0188367{col 45}{space 1}   -4.10{col 54}{space 3}0.000{col 62}{space 4} -.114201{col 75}{space 3}-.0402494
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.1642353{col 34}{space 2} .1569693{col 45}{space 1}   -1.05{col 54}{space 3}0.296{col 62}{space 4}-.4723603{col 75}{space 3} .1438896
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .2024069{col 34}{space 2} .1424468{col 45}{space 1}    1.42{col 54}{space 3}0.156{col 62}{space 4} -.077211{col 75}{space 3} .4820249
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1135471{col 34}{space 2} .0167176{col 45}{space 1}    6.79{col 54}{space 3}0.000{col 62}{space 4} .0807311{col 75}{space 3} .1463631
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}&\\
{res}{txt}
{com}. 
.         tex Electoral victory & `beta1_donate_15any' & `beta1_b5' & `beta1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `pval2_donate_15any' & `pval2_b5' & `pval2_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`ser1_donate_15any',`ser2_donate_15any'] & [`ser1_b5',`ser2_b5'] & [`ser1_b2b',`ser2_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}&\\
{res}{txt}
{com}. 
.     tex Electoral victory & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `Neff_donate_15any' & `Neff_b5' & `Neff_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `em1_donate_15any' & `em1_b5' & `em1_b2b' \\
.         tex Bandwidth & `bw_donate_15any' & `bw_b5' & `bw_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. 95\% robust confidence intervals and robust p-values with clustering at the municipality level are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\Table2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/Table2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/Table2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\Table2.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on benefits to donors{c )-}\label{c -(}tab:table_benefits{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l H H c c c c{c )-} \hline
{res}{txt}
{com}.         tex Outcome:& &&\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Receive contract{c )-}&Receive contract& Runs in 2015\\
{res}{txt}
{com}.         tex &  & &\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} & (outside)& \\
{res}{txt}
{com}.         tex & Non-family &Family & Non-Family &Family  & Family &Family \\
{res}{txt}
{com}.         tex & (1) & (2) & (1) & (2)& (3) & (4)\\ \hline
{res}{txt}
{com}.         tex & & & & & &\\
{res}{txt}
{com}. 
.         
.         *Model 1
.         foreach x in  contract{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum nf`x' if e(sample)
{txt}  4{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 rdrobust nf`x' margin_victory , vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local nfbw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local nfNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local nfN_`x' = `e(N)'
{txt} 10{com}.                 local nfbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local nfbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local nfser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local nfser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local nfem1_`x' = (`nfbeta1_`x''/`nfmean_`x'')*100 
{txt} 15{com}.                         local nfem1_`x' : di %5.2f `nfem1_`x''
{txt} 16{com}.                         
.                 *P-values
.                 local nfpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar nfpval2_`x' = e(pv_rb)
{txt} 18{com}.                 
.                 regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt} 20{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 25{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 27{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 28{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 29{com}.                 
. 
.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      201{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.110{col 34}    0.110
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      256{col 34}      304

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08876{col 33} .04149{col 43}2.1394{col 52}0.032{col 60} .007442{col 73} .170068
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}1.9436{col 52}0.052{col 60}-.000802{col 73} .190711
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       823
                                                {txt}F(3, 614)         =  {res}     8.21
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0256
                                                {txt}Root MSE          =    {res} .20661

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}          nfcontract{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .0565465{col 34}{space 2} .0227793{col 45}{space 1}    2.48{col 54}{space 3}0.013{col 62}{space 4} .0118118{col 75}{space 3} .1012813
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .1005297{col 34}{space 2} .2285033{col 45}{space 1}    0.44{col 54}{space 3}0.660{col 62}{space 4}-.3482131{col 75}{space 3} .5492725
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0053472{col 34}{space 2} .1304305{col 45}{space 1}    0.04{col 54}{space 3}0.967{col 62}{space 4}-.2507968{col 75}{space 3} .2614912
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0604674{col 34}{space 2} .0146929{col 45}{space 1}    4.12{col 54}{space 3}0.000{col 62}{space 4}  .031613{col 75}{space 3} .0893218
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 
.                 *Family
.                 *Regressions
. 
. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. 
. 
.         foreach x in   contract got_above_ext runs_any{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 rdrobust f`x' margin_victory , vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local fbw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local fNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local fN_`x' = `e(N)'
{txt} 10{com}.                 local fbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local fbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local fser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local fser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local fem1_`x' = (`fbeta1_`x''/`fmean_`x'')*100 
{txt} 15{com}.                         local fem1_`x' : di %5.2f `fem1_`x''
{txt} 16{com}.                         
.                 *P-values
.                 local fpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar fpval2_`x' = e(pv_rb)
{txt} 18{com}.                 
.                 regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt} 20{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 25{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 27{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 28{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 29{com}.                 
. 
.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       86{col 34}      103{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.030{col 34}    0.030
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.115{col 34}    0.115
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      314

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00086{col 33} .00086{col 43}-0.9998{col 52}0.317{col 60}-.002554{col 73} .000828
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.4185{col 52}0.676{col 60}-.002828{col 73} .001833
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       778
                                                {txt}F(3, 612)         =  {res}     0.58
                                                {txt}Prob > F          = {res}    0.6297
                                                {txt}R-squared         = {res}    0.0032
                                                {txt}Root MSE          =    {res} .04897

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           fcontract{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .0021715{col 34}{space 2} .0052433{col 45}{space 1}    0.41{col 54}{space 3}0.679{col 62}{space 4}-.0081255{col 75}{space 3} .0124685
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .0591687{col 34}{space 2} .0684239{col 45}{space 1}    0.86{col 54}{space 3}0.388{col 62}{space 4}-.0752055{col 75}{space 3} .1935429
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} -.061742{col 34}{space 2} .0684392{col 45}{space 1}   -0.90{col 54}{space 3}0.367{col 62}{space 4}-.1961462{col 75}{space 3} .0726622
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0006734{col 34}{space 2} .0046748{col 45}{space 1}    0.14{col 54}{space 3}0.886{col 62}{space 4}-.0085073{col 75}{space 3} .0098541
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      223{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      315

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03591{col 33} .04692{col 43}-0.7652{col 52}0.444{col 60}-.127877{col 73} .056061
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.8651{col 52}0.387{col 60}-.154678{col 73} .059948
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       778
                                                {txt}F(3, 612)         =  {res}     2.22
                                                {txt}Prob > F          = {res}    0.0848
                                                {txt}R-squared         = {res}    0.0084
                                                {txt}Root MSE          =    {res} .23648

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}      fgot_above_ext{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0046017{col 34}{space 2} .0255257{col 45}{space 1}   -0.18{col 54}{space 3}0.857{col 62}{space 4}-.0547303{col 75}{space 3}  .045527
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}  .256227{col 34}{space 2} .2589094{col 45}{space 1}    0.99{col 54}{space 3}0.323{col 62}{space 4}-.2522316{col 75}{space 3} .7646857
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.3226398{col 34}{space 2} .2207331{col 45}{space 1}   -1.46{col 54}{space 3}0.144{col 62}{space 4} -.756126{col 75}{space 3} .1108465
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0919979{col 34}{space 2} .0198886{col 45}{space 1}    4.63{col 54}{space 3}0.000{col 62}{space 4} .0529397{col 75}{space 3} .1310562
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      202{col 34}      254{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.082{col 34}    0.082
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      265{col 34}      319

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01966{col 33} .02008{col 43}-0.9789{col 52}0.328{col 60} -.05902{col 73} .019702
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.8473{col 52}0.397{col 60}-.060815{col 73} .024104
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       778
                                                {txt}F(3, 612)         =  {res}     0.56
                                                {txt}Prob > F          = {res}    0.6431
                                                {txt}R-squared         = {res}    0.0029
                                                {txt}Root MSE          =    {res} .09755

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           fruns_any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0110574{col 34}{space 2} .0130359{col 45}{space 1}   -0.85{col 54}{space 3}0.397{col 62}{space 4}-.0366579{col 75}{space 3} .0145431
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .0342766{col 34}{space 2} .1234866{col 45}{space 1}    0.28{col 54}{space 3}0.781{col 62}{space 4}-.2082321{col 75}{space 3} .2767854
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0577678{col 34}{space 2} .0933564{col 45}{space 1}    0.62{col 54}{space 3}0.536{col 62}{space 4}-.1255699{col 75}{space 3} .2411054
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0175813{col 34}{space 2}  .011605{col 45}{space 1}    1.51{col 54}{space 3}0.130{col 62}{space 4}-.0052091{col 75}{space 3} .0403718
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 
.         
. 
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}&&&&\\
{res}{txt}
{com}. 
.         tex Electoral victory & `nfbeta1_total_cont_num_d' &  `fbeta1_total_cont_num_d'& `nfbeta1_contract' & `fbeta1_contract' & `fbeta1_got_above_ext' & `fbeta1_runs_any' \\
{res}{txt}
{com}.         
.         tex \ \ \ \ Robust p-value & `nfpval2_total_cont_num_d' &  `fpval2_total_cont_num_d' & `nfpval2_contract' & `fpval2_contract' & `fpval2_got_above_ext' & `fpval2_runs_any' \\
{res}{txt}
{com}.         
.         
.         
.         tex \ \ \ \ CI 95\%  & [`nfser1_total_cont_num_d',`nfser2_total_cont_num_d'] & [`fser1_total_cont_num_d',`fser2_total_cont_num_d'] &  [`nfser1_contract',`nfser2_contract'] & [`fser1_contract',`fser2_contract'] & [`fser1_got_above_ext',`fser2_got_above_ext'] & [`fser1_runs_any',`fser2_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}&&&&\\
{res}{txt}
{com}. 
.         tex Electoral victory & `nfb1_total_cont_num_d' &  `fb1_total_cont_num_d'& `nfb1_contract' & `fb1_contract' & `fb1_got_above_ext' & `fb1_runs_any' \\
{res}{txt}
{com}.         
.         tex \ \ \ \  p-value & `nfp_v_total_cont_num_d' &  `fp_v_total_cont_num_d' & `nfp_v_contract' & `fp_v_contract' & `fp_v_got_above_ext' & `fp_v_runs_any' \\
{res}{txt}
{com}.         
.         
.         
.         tex \ \ \ \ CI 95\%  & [`nflci_total_cont_num_d',`nflci_total_cont_num_d'] & [`flci_total_cont_num_d',`fuci_total_cont_num_d'] &  [`nflci_contract',`nfuci_contract'] & [`flci_contract',`fuci_contract'] & [`flci_got_above_ext',`fuci_got_above_ext'] & [`flci_runs_any',`fuci_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations &`nfN_total_cont_num_d' &  `fN_total_cont_num_d' & `nfN_contract'& `fN_contract' & `fN_got_above_ext' & `fN_runs_any' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `nfNeff_total_cont_num_d' & `fNeff_total_cont_num_d' & `nfNeff_contract'& `fNeff_contract' & `fNeff_got_above_ext' & `fNeff_runs_any' \\
{res}{txt}
{com}.         tex Mean & `nfmean_total_cont_num_d' &`fmean_total_cont_num_d'  &  `nfmean_contract' & `fmean_contract' & `fmean_got_above_ext' & `fmean_runs_any' \\
{res}{txt}
{com}.         tex Bandwidth & `nfbw_total_cont_num_d' &  `fbw_total_cont_num_d' &`nfbw_contract' & `fbw_contract' & `fbw_got_above_ext' & `fbw_runs_any' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level and 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. The parametric linear model specification includes interaction of the treatment with running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\Table3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear     
{txt}
{com}. 
. gen treat=0
{txt}
{com}.                 replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}.                 replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
.                 gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/Table3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/Table3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\Table3.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members){c )-}\label{c -(}tab:donation_fam_nofam{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor & b2 \\ 
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}&\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 
. 
.                 
. 
.                 
.                 *Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly: regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                         
.                 rdrobust f`x' margin_victory ,  vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local fbw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local fNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local fN_`x' = `e(N)'
{txt} 10{com}.                 local fbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local fbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local fser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local fser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local fem1_`x' = (`fbeta1_`x''/`fmean_`x'')*100 
{txt} 15{com}.                         local fem1_`x' : di %5.2f `fem1_`x''
{txt} 16{com}.                         
.                 *P-values
.                 local fpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar fpval2_`x' = e(pv_rb)
{txt} 18{com}.                 
.                 
.                 regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt} 20{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 25{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 27{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 28{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 29{com}. 
. 
. 
.                 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly: regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 30{com}.                 quietly sum nf`x' if e(sample)
{txt} 31{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt} 32{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt} 33{com}. 
.                 rdrobust nf`x' margin_victory ,  vce(cluster muni_code)
{txt} 34{com}. 
.                 *Local's for the table
.                 local nfbw_`x' : di %5.2f `e(h_l)'
{txt} 35{com}.                 local nfNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt} 36{com}.                 local nfN_`x' = `e(N)'
{txt} 37{com}.                 local nfbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 38{com}.                 local nfbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 39{com}. 
.                 *Confidence intervals
.                         local nfser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 40{com}.                         local nfser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 41{com}.                         
. /* HERE*/       local nfem1_`x' = (`nfbeta1_`x''/`nfmean_`x'')*100 
{txt} 42{com}.                         local nfem1_`x' : di %5.2f `nfem1_`x''
{txt} 43{com}.                         
.                 *P-values
.                 local nfpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 44{com}.                 scalar nfpval2_`x' = e(pv_rb)
{txt} 45{com}.                 
.                 regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 46{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt} 47{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt} 48{com}. 
.                 matrix b = e(b)
{txt} 49{com}.                 matrix v = e(V)
{txt} 50{com}.                 matrix res=r(table)
{txt} 51{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 52{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 53{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 54{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 55{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 56{com}. 
.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      238{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      251{col 34}      306

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.2015{col 33} .05735{col 43}-3.5135{col 52}0.000{col 60}-.313908{col 73}-.089097
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-2.9758{col 52}0.003{col 60}-.335614{col 73}-.069073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       778
                                                {txt}F(3, 612)         =  {res}    19.45
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0812
                                                {txt}Root MSE          =    {res} .24051

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}       fdonate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.1642552{col 34}{space 2} .0322701{col 45}{space 1}   -5.09{col 54}{space 3}0.000{col 62}{space 4}-.2276288{col 75}{space 3}-.1008816
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.0974813{col 34}{space 2} .3172197{col 45}{space 1}   -0.31{col 54}{space 3}0.759{col 62}{space 4}-.7204525{col 75}{space 3}   .52549
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1839677{col 34}{space 2} .2997765{col 45}{space 1}    0.61{col 54}{space 3}0.540{col 62}{space 4}-.4047478{col 75}{space 3} .7726831
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1829233{col 34}{space 2} .0307292{col 45}{space 1}    5.95{col 54}{space 3}0.000{col 62}{space 4} .1225759{col 75}{space 3} .2432708
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      245{col 34}      287{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      404

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05392{col 33} .04088{col 43}-1.3189{col 52}0.187{col 60}-.134041{col 73} .026207
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.2320{col 52}0.218{col 60}-.153548{col 73} .035019
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       823
                                                {txt}F(3, 614)         =  {res}     2.16
                                                {txt}Prob > F          = {res}    0.0919
                                                {txt}R-squared         = {res}    0.0085
                                                {txt}Root MSE          =    {res} .23064

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}      nfdonate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0591406{col 34}{space 2} .0259607{col 45}{space 1}   -2.28{col 54}{space 3}0.023{col 62}{space 4}-.1101231{col 75}{space 3}-.0081581
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.0634349{col 34}{space 2} .2151847{col 45}{space 1}   -0.29{col 54}{space 3}0.768{col 62}{space 4}-.4860222{col 75}{space 3} .3591523
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1437804{col 34}{space 2} .1686193{col 45}{space 1}    0.85{col 54}{space 3}0.394{col 62}{space 4}-.1873602{col 75}{space 3} .4749209
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1403564{col 34}{space 2} .0212434{col 45}{space 1}    6.61{col 54}{space 3}0.000{col 62}{space 4} .0986379{col 75}{space 3} .1820749
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      206{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      280{col 34}      349

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17469{col 33} .04849{col 43}-3.6023{col 52}0.000{col 60} -.26974{col 73}-.079645
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.2416{col 52}0.001{col 60} -.29583{col 73} -.07289
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       778
                                                {txt}F(3, 612)         =  {res}    18.83
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0796
                                                {txt}Root MSE          =    {res} .21814

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                 fb5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.1320505{col 34}{space 2}  .028707{col 45}{space 1}   -4.60{col 54}{space 3}0.000{col 62}{space 4}-.1884267{col 75}{space 3}-.0756743
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} -.070835{col 34}{space 2}  .285709{col 45}{space 1}   -0.25{col 54}{space 3}0.804{col 62}{space 4}-.6319241{col 75}{space 3}  .490254
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0562602{col 34}{space 2} .2811479{col 45}{space 1}    0.20{col 54}{space 3}0.841{col 62}{space 4}-.4958714{col 75}{space 3} .6083918
{txt}{space 15}_cons {c |}{col 22}{res}{space 2}  .147196{col 34}{space 2} .0279643{col 45}{space 1}    5.26{col 54}{space 3}0.000{col 62}{space 4} .0922783{col 75}{space 3} .2021137
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      155{col 34}      175{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      247{col 34}      291

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07969{col 33} .05297{col 43}-1.5044{col 52}0.132{col 60}-.183502{col 73} .024129
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.6132{col 52}0.107{col 60}-.221849{col 73} .021531
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       823
                                                {txt}F(3, 614)         =  {res}     1.36
                                                {txt}Prob > F          = {res}    0.2526
                                                {txt}R-squared         = {res}    0.0047
                                                {txt}Root MSE          =    {res} .19102

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                nfb5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0410037{col 34}{space 2} .0205233{col 45}{space 1}   -2.00{col 54}{space 3}0.046{col 62}{space 4} -.081308{col 75}{space 3}-.0006993
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.1105313{col 34}{space 2} .1729822{col 45}{space 1}   -0.64{col 54}{space 3}0.523{col 62}{space 4}-.4502397{col 75}{space 3} .2291771
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1811109{col 34}{space 2} .1272965{col 45}{space 1}    1.42{col 54}{space 3}0.155{col 62}{space 4}-.0688784{col 75}{space 3} .4311003
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0912884{col 34}{space 2} .0170406{col 45}{space 1}    5.36{col 54}{space 3}0.000{col 62}{space 4} .0578235{col 75}{space 3} .1247534
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. 
. 
.                 
. 
.         *Continue table
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `fbeta1_donate_15any' & `fbeta1_b5' & `fbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fpval2_donate_15any' & `fpval2_b5' & `fpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`fser1_donate_15any',`fser2_donate_15any'] & [`fser1_b5',`fser2_b5'] & [`fser1_b3',`fser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v_donate_15any' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_15any',`fuci_donate_15any'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' & `fN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `fNeff_donate_15any' & `fNeff_b5' & `fNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' & `fmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `fbw_donate_15any' & `fbw_b5' & `fbw_b3' \\ 
{res}{txt}
{com}.         
.         tex & & & \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}. 
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfbeta1_donate_15any' & `nfbeta1_b5' & `nfbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfpval2_donate_15any' & `nfpval2_b5' & `nfpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nfser1_donate_15any',`nfser2_donate_15any'] & [`nfser1_b5',`nfser2_b5'] & [`nfser1_b3',`nfser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfb1_donate_15any' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfp_v_donate_15any' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_15any',`nfuci_donate_15any'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_15any' & `nfN_b5' & `nfN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `nfNeff_donate_15any' & `nfNeff_b5' & `nfNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_15any' & `nfmean_b5' & `nfmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `nfbw_donate_15any' & `nfbw_b5' & `nfbw_b3' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level and 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with the running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\Table4.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==1&family==0
{txt}(5,397 observations deleted)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/Table4.tex"
{txt}
{com}.         texdoc init "$dir/Tables/Table4.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\Table4.tex)
{res}{txt}
{com}. 
. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effects of contracts on next election donations (Non-family members){c )-}\label{c -(}tab:contracts_donation{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}lHcc c Hcc c HHH{c )-} \hline
{res}{txt}
{com}.         *tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Only mayor{c )-} \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} \cline{c -(}10-12{c )-}
.         tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} 
{res}{txt}
{com}.         tex & (1) & (1) & (2) && (4) & (3) & (4) && (7) & (5) & (6) \\ \hline
{res}{txt}
{com}.         tex & & & & & & & & & & &\\
{res}{txt}
{com}.         
.         
.         
.         replace b5=. if b2!=0
{txt}(113 real changes made, 113 to missing)

{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  7{com}.                 
.                 local N_`x' : di %5.0f e(N)
{txt}  8{com}.                 local R2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.                 *T-statistics
.                 local t1_`x' = `b1_`x''/`se1_`x''
{txt} 18{com}.                 local t1_`x' : di %5.3f  `t1_`x''
{txt} 19{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 20{com}.                 scalar pval1_`x' = ttail(`df', abs(`t1_`x''))*2         
{txt} 21{com}. 
. 
.         
.         
.                 *Reg with FE
.                 areg `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 22{com}.                 
.                 local dN_`x' : di %5.0f e(N)
{txt} 23{com}.                 local dR2_`x' : di %5.3f e(r2)
{txt} 24{com}.                 
.                 matrix db = e(b)
{txt} 25{com}.                 matrix dv = e(V)
{txt} 26{com}.                 matrix dres=r(table)
{txt} 27{com}.                 
.                 local db1_`x' : di %5.3f db[1,1]
{txt} 28{com}.                 local dse1_`x' : di %5.3f sqrt(dv[1,1])
{txt} 29{com}.                 local dp_v_`x' :di %5.3f dres[4,1]
{txt} 30{com}.                 local duci_`x': di %5.3f dres[6,1]
{txt} 31{com}.                 local dlci_`x': di %5.3f dres[5,1]
{txt} 32{com}.                                 
.                 *T-statistics
.                 local dt1_`x' = `db1_`x''/`dse1_`x''
{txt} 33{com}.                 local dt1_`x' : di %5.3f  `dt1_`x''
{txt} 34{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 35{com}.                 scalar dpval1_`x' = ttail(`df', abs(`dt1_`x''))*2
{txt} 36{com}. 
. 
.                         
.         {c )-}       

{txt}Linear regression                               Number of obs     = {res}     3,125
                                                {txt}{help j_robustsingular:F(10, 488) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0292
                                                {txt}Root MSE          =    {res} .27874

{txt}{ralign 82:(Std. err. adjusted for {res:489} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0459101{col 30}{space 2} .0172699{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0119776{col 71}{space 3} .0798427
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0233185{col 30}{space 2} .0304363{col 41}{space 1}    0.77{col 50}{space 3}0.444{col 58}{space 4}-.0364838{col 71}{space 3} .0831208
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .9543676{col 30}{space 2} .0248216{col 41}{space 1}   38.45{col 50}{space 3}0.000{col 58}{space 4} .9055972{col 71}{space 3} 1.003138
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0047958{col 30}{space 2} .0322357{col 41}{space 1}   -0.15{col 50}{space 3}0.882{col 58}{space 4}-.0681336{col 71}{space 3}  .058542
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0059467{col 30}{space 2} .0063666{col 41}{space 1}   -0.93{col 50}{space 3}0.351{col 58}{space 4}-.0184559{col 71}{space 3} .0065626
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}  .009883{col 30}{space 2} .0173914{col 41}{space 1}    0.57{col 50}{space 3}0.570{col 58}{space 4}-.0242884{col 71}{space 3} .0440543
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0132439{col 30}{space 2} .0148421{col 41}{space 1}    0.89{col 50}{space 3}0.373{col 58}{space 4}-.0159184{col 71}{space 3} .0424061
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0013072{col 30}{space 2}  .001193{col 41}{space 1}    1.10{col 50}{space 3}0.274{col 58}{space 4}-.0010368{col 71}{space 3} .0036512
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0479365{col 30}{space 2} .0098527{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0285775{col 71}{space 3} .0672955
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0038046{col 30}{space 2} .0630494{col 41}{space 1}   -0.06{col 50}{space 3}0.952{col 58}{space 4}-.1276863{col 71}{space 3} .1200772
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0381358{col 30}{space 2} .0295302{col 41}{space 1}   -1.29{col 50}{space 3}0.197{col 58}{space 4}-.0961579{col 71}{space 3} .0198863
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0061357{col 30}{space 2} .0325375{col 41}{space 1}   -0.19{col 50}{space 3}0.851{col 58}{space 4}-.0700666{col 71}{space 3} .0577952
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:3,125}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:489}
{txt}{col 53}{lalign 17:F({res:5}, {res:488})}{col 70} = {res}{ralign 6:3.94}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0016}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2259}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0809}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2708}

{txt}{ralign 82:(Std. err. adjusted for {res:489} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0435863{col 30}{space 2} .0212075{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0019169{col 71}{space 3} .0852556
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0061196{col 30}{space 2} .0046968{col 41}{space 1}   -1.30{col 50}{space 3}0.193{col 58}{space 4} -.015348{col 71}{space 3} .0031088
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0212937{col 30}{space 2} .0259942{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0297807{col 71}{space 3}  .072368
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0087971{col 30}{space 2} .0394672{col 41}{space 1}   -0.22{col 50}{space 3}0.824{col 58}{space 4}-.0863437{col 71}{space 3} .0687494
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0894913{col 30}{space 2}  .043302{col 41}{space 1}   -2.07{col 50}{space 3}0.039{col 58}{space 4}-.1745727{col 71}{space 3}  -.00441
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   .09211{col 30}{space 2} .0630481{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0317693{col 71}{space 3} .2159893
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res}     3,013
                                                {txt}F(10, 484)        =  {res}     4.80
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0375
                                                {txt}Root MSE          =    {res} .22105

{txt}{ralign 82:(Std. err. adjusted for {res:485} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0287647{col 30}{space 2} .0135172{col 41}{space 1}    2.13{col 50}{space 3}0.034{col 58}{space 4}  .002205{col 71}{space 3} .0553244
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0141981{col 30}{space 2} .0249511{col 41}{space 1}    0.57{col 50}{space 3}0.570{col 58}{space 4}-.0348278{col 71}{space 3}  .063224
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .0103269{col 30}{space 2} .0256707{col 41}{space 1}    0.40{col 50}{space 3}0.688{col 58}{space 4} -.040113{col 71}{space 3} .0607668
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0099663{col 30}{space 2} .0058131{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.0213882{col 71}{space 3} .0014557
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0185636{col 30}{space 2} .0136253{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.0082084{col 71}{space 3} .0453355
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0159272{col 30}{space 2} .0099741{col 41}{space 1}    1.60{col 50}{space 3}0.111{col 58}{space 4}-.0036708{col 71}{space 3} .0355252
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0009339{col 30}{space 2}  .000813{col 41}{space 1}    1.15{col 50}{space 3}0.251{col 58}{space 4}-.0006636{col 71}{space 3} .0025314
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0462281{col 30}{space 2} .0088884{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .0287634{col 71}{space 3} .0636928
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0286768{col 30}{space 2} .0627499{col 41}{space 1}    0.46{col 50}{space 3}0.648{col 58}{space 4}-.0946192{col 71}{space 3} .1519727
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0277199{col 30}{space 2} .0275611{col 41}{space 1}   -1.01{col 50}{space 3}0.315{col 58}{space 4}-.0818741{col 71}{space 3} .0264343
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0440619{col 30}{space 2}   .02576{col 41}{space 1}   -1.71{col 50}{space 3}0.088{col 58}{space 4}-.0946771{col 71}{space 3} .0065532
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:3,013}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:485}
{txt}{col 53}{lalign 17:F({res:5}, {res:484})}{col 70} = {res}{ralign 6:4.04}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0013}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2524}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1075}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2125}

{txt}{ralign 82:(Std. err. adjusted for {res:485} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0269444{col 30}{space 2} .0157447{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0039921{col 71}{space 3} .0578808
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0046442{col 30}{space 2} .0035804{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-.0116793{col 71}{space 3} .0023909
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0301934{col 30}{space 2} .0208409{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0107563{col 71}{space 3} .0711432
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}  .016374{col 30}{space 2} .0365658{col 41}{space 1}    0.45{col 50}{space 3}0.655{col 58}{space 4}-.0554734{col 71}{space 3} .0882214
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0974122{col 30}{space 2} .0400848{col 41}{space 1}   -2.43{col 50}{space 3}0.015{col 58}{space 4} -.176174{col 71}{space 3}-.0186505
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0389261{col 30}{space 2} .0486328{col 41}{space 1}    0.80{col 50}{space 3}0.424{col 58}{space 4}-.0566315{col 71}{space 3} .1344836
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         tex  Contract & `ub1_donate_15any' & `b1_donate_15any' & `db1_donate_15any' && `ub1_b5' & `b1_b5' & `db1_b5' && `ub1_b3' & `b1_b3' & `db1_b3' \\
{res}{txt}
{com}.         tex  \ \ \ \ p-value & `up_v_donate_15any' & `p_v_donate_15any' & `dp_v_donate_15any' && `up_v_b5' & `p_v_b5' & `dp_v_b5' && `up_v_b3' & `p_v_b3' & `dp_v_b3' \\ 
{res}{txt}
{com}.         tex  \ \ \ \ CI 95\% & [`ulci_donate_15any',`uuci_donate_15any']& [`lci_donate_15any',`uci_donate_15any'] & [`dlci_donate_15any',`duci_donate_15any'] && [`ulci_b5',`uuci_b5'] & [`lci_b5',`uci_b5'] & [`dlci_b5',`duci_b5'] && [`ulci_b3',`uuci_b3'] & [`lci_b3',`uci_b3'] & [`dlci_b3',`duci_b3'] \\ \hline
{res}{txt}
{com}.         tex  % & (`use1_donate_15any') & (`se1_donate_15any') & (`dse1_donate_15any') && (`use1_b5') & (`se1_b5') & (`dse1_b5') && (`use1_b3') & (`se1_b3') & (`dse1_b3') \\    
{res}{txt}
{com}.         
.         tex Observations & `uN_donate_15any' & `N_donate_15any' & `dN_donate_15any' && `uN_b5' & `N_b5' & `dN_b5' && `uN_b3' & `N_b3' & `dN_b3' \\
{res}{txt}
{com}.         tex Mean &  `mean_donate_15any' & `mean_donate_15any' &  `mean_donate_15any' && `mean_b5' & `mean_b5' &`mean_b5'&& `mean_b3' & `mean_b3' & `mean_b3' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `fem1_donate_15any' & `fem1_b5' & `fem1_b3' \\
.         tex Controls mayor& no & yes & no && no & yes &no && no & yes & no \\
{res}{txt}
{com}.         tex Controls donor& no & yes & yes && no & yes &yes && no & yes & yes \\
{res}{txt}
{com}.         tex Municipality FE & no & no & yes &&no & no & yes && no & no & yes \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}150mm{c )-}{c -(}  \footnotesize{c -(}
{res}{txt}
{com}.         tex Ordinary least squares (OLS) estimates of the effect of receiving a contract on donating in the next election. The sample includes non-family donors to the mayor. `Controls mayor' denotes candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, and non family donations as a fraction of campaign revenue. `Controls donor' denotes logged value of donation, donated above legal limit, sanctioned, and rank of donation among all family and non-family donors. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableA1.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableA1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableA1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableA1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on donation type{c )-}\label{c -(}tab:bal_mis{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Has non-family donors  & Has family donors & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in dat_no_fam dat_fam {c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly sum `x' if margin_victory!=.
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' margin_victory ,  p(1) vce(cluster muni_code)
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %5.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_bc)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 18{com}.                 scalar pval2_`x' = e(pv_rb)
{txt} 19{com}. 
.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      293{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.569{col 34}    0.569
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      381{col 34}      445

Outcome: dat_no_fam. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .02291{col 33} .08498{col 43}0.2696{col 52}0.787{col 60}-.143648{col 73} .189475
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}0.4967{col 52}0.619{col 60}-.143654{col 73} .241175
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      276{col 34}      317{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.622{col 34}    0.622
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      380{col 34}      443

Outcome: dat_fam. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01433{col 33} .08163{col 43}0.1755{col 52}0.861{col 60} -.14567{col 73} .174327
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}0.0331{col 52}0.974{col 60} -.18608{col 73} .192482
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

{com}.         
. 
. 
.         *Continue table
.         tex Electoral victory & `beta1_dat_no_fam' & `beta1_dat_fam' & `beta1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `pval2_dat_no_fam' & `pval2_dat_fam' & `pval2_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`ser1_dat_no_fam',`ser2_dat_no_fam'] & [`ser1_dat_fam',`ser2_dat_fam'] & [`ser1_b2b',`ser2_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `N_dat_no_fam' & `N_dat_fam' & `N_b2b' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `Neff_dat_no_fam' & `Neff_dat_fam' & `Neff_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_dat_no_fam' & `mean_dat_fam' & `mean_b2b' \\
{res}{txt}
{com}.         tex Effect Mean(\%) & `em1_dat_no_fam' & `em1_dat_fam' & `em1_b2b' \\
{res}{txt}
{com}.         tex Bandwidth & `bw_dat_no_fam' & `bw_dat_fam' & `bw_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableA2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableA2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableA2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableA2.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Running in next mayoral election (runner up and third-place candidate){c )-}\label{c -(}tab:second_third{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c {c )-} \hline
{res}{txt}
{com}.         tex Outcome& Running again  \\
{res}{txt}
{com}.         tex & (1)  \\ \hline
{res}{txt}
{com}.         tex &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in runs{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly sum `x' if  vote_margin2_3!=.
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' vote_margin2_3,  p(1) vce(cluster muni_code)
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %5.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_bc)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 18{com}.                 scalar pval2_`x' = e(pv_rb)
{txt} 19{com}.                         
. 
.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       753
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      369{col 34}      384{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      222{col 34}      220{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.330{col 34}    0.330
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.526{col 34}    0.526
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.626{col 34}    0.626
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      293{col 34}      299

Outcome: runs. Running variable: vote_margin2_3.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .21847{col 33} .08535{col 43}2.5598{col 52}0.010{col 60} .051191{col 73}  .38574
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}2.3066{col 52}0.021{col 60} .034414{col 73} .423626
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

{com}.         
. 
. 
.         *Continue table
.         tex Second & `beta1_runs'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `pval2_runs'  \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`ser1_runs',`ser2_runs'] \\
{res}{txt}
{com}.         tex & \\
{res}{txt}
{com}.         
.         tex Observations & `N_runs'  \\
{res}{txt}
{com}.         tex Bandwidth obs. & `Neff_runs'  \\
{res}{txt}
{com}.         tex Mean & `mean_runs' \\
{res}{txt}
{com}.         tex Bandwidth & `bw_runs' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableA3.do"
{txt}
{com}.         clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==1&family==0
{txt}(5,397 observations deleted)

{com}. 
. replace b5=. if b2!=0
{txt}(113 real changes made, 113 to missing)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableA3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableA3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableA3.tex)
{res}{txt}
{com}. 
. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Contracts and next election donations (non-family members: logit results){c )-}\label{c -(}tab:contracts_donation_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}lHcc c Hcc c HHH{c )-} \hline
{res}{txt}
{com}.         *tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Only mayor{c )-} \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} \cline{c -(}10-12{c )-}
.         tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} 
{res}{txt}
{com}.         tex & (1) & (1) & (2) && (4) & (3) & (4) && (7) & (5) & (6) \\ \hline
{res}{txt}
{com}.         tex & & & & & & & & & & &\\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: logit `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 logit `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}  7{com}.                 
.                 local N_`x' : di %5.0f e(N)
{txt}  8{com}.                 local ll_`x' : di %5.3f e(ll)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 17{com}. 
. 
.                 
.                 *T-statistics
.                 local t1_`x' = `b1_`x''/`se1_`x''
{txt} 18{com}.                 local t1_`x' : di %5.3f  `t1_`x''
{txt} 19{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 20{com}.                 scalar pval1_`x' = ttail(`df', abs(`t1_`x''))*2         
{txt} 21{com}. 
.                 
. 
.                 
.                 *Reg with FE
.                 clogit `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample),group(muni_code) vce(cluster muni_code)
{txt} 22{com}.                 
.                 local dN_`x' : di %5.0f e(N)
{txt} 23{com}.                 local dll_`x' : di %5.3f e(ll)
{txt} 24{com}.                 
.                 matrix db = e(b)
{txt} 25{com}.                 matrix dv = e(V)
{txt} 26{com}.                 matrix dres=r(table)
{txt} 27{com}.                 
.                 local db1_`x' : di %5.3f db[1,1]
{txt} 28{com}.                 local dse1_`x' : di %5.3f sqrt(dv[1,1])
{txt} 29{com}.                 local dp_v_`x' :di %5.3f dres[4,1]
{txt} 30{com}.                 local duci_`x': di %5.3f dres[6,1]
{txt} 31{com}.                 local dlci_`x': di %5.3f dres[5,1]
{txt} 32{com}. 
.                                 
.                 *T-statistics
.                 local dt1_`x' = `db1_`x''/`dse1_`x''
{txt} 33{com}.                 local dt1_`x' : di %5.3f  `dt1_`x''
{txt} 34{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 35{com}.                 scalar dpval1_`x' = ttail(`df', abs(`dt1_`x''))*2
{txt} 36{com}. 
. 
.         {c )-}       

{txt}note: {bf:ilegal} != 0 predicts success perfectly;
      {bf:ilegal} omitted and 1 obs not used.

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-923.76966}  
Iteration 1:{space 3}log pseudolikelihood = {res:-889.10758}  
Iteration 2:{space 3}log pseudolikelihood = {res:-886.04126}  
Iteration 3:{space 3}log pseudolikelihood = {res:-886.03072}  
Iteration 4:{space 3}log pseudolikelihood = {res:-886.03072}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:3,124}
{txt}{col 57}{lalign 13:Wald chi2({res:10})}{col 70} = {res}{ralign 6:43.16}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-886.03072}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0409}

{txt}{ralign 82:(Std. err. adjusted for {res:488} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .5392784{col 30}{space 2} .1739191{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .1984032{col 71}{space 3} .8801537
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .2449534{col 30}{space 2} .2752332{col 41}{space 1}    0.89{col 50}{space 3}0.373{col 58}{space 4}-.2944938{col 71}{space 3} .7844006
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.1102521{col 30}{space 2} .4092107{col 41}{space 1}   -0.27{col 50}{space 3}0.788{col 58}{space 4}-.9122903{col 71}{space 3} .6917861
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0496341{col 30}{space 2} .0701033{col 41}{space 1}   -0.71{col 50}{space 3}0.479{col 58}{space 4}-.1870341{col 71}{space 3} .0877658
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0987341{col 30}{space 2} .2099866{col 41}{space 1}    0.47{col 50}{space 3}0.638{col 58}{space 4} -.312832{col 71}{space 3} .5103002
{txt}{space 10}center {c |}{col 18}{res}{space 2} .2140712{col 30}{space 2} .2209521{col 41}{space 1}    0.97{col 50}{space 3}0.333{col 58}{space 4} -.218987{col 71}{space 3} .6471294
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0159268{col 30}{space 2} .0151335{col 41}{space 1}    1.05{col 50}{space 3}0.293{col 58}{space 4}-.0137343{col 71}{space 3}  .045588
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .5458588{col 30}{space 2} .0922599{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .3650328{col 71}{space 3} .7266848
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0749701{col 30}{space 2} 1.033056{col 41}{space 1}   -0.07{col 50}{space 3}0.942{col 58}{space 4}-2.099722{col 71}{space 3} 1.949782
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.366277{col 30}{space 2} .3209183{col 41}{space 1}   -1.14{col 50}{space 3}0.254{col 58}{space 4}-.9952654{col 71}{space 3} .2627113
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-3.554819{col 30}{space 2} .4099434{col 41}{space 1}   -8.67{col 50}{space 3}0.000{col 58}{space 4}-4.358294{col 71}{space 3}-2.751345
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
note: multiple positive outcomes within groups encountered.
note: 366 groups (1,516 obs) omitted because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-494.09464}  
Iteration 1:{space 3}log pseudolikelihood = {res:-493.10692}  
Iteration 2:{space 3}log pseudolikelihood = {res:-493.10469}  
Iteration 3:{space 3}log pseudolikelihood = {res:-493.10469}  
{res}
{txt}{col 1}Conditional (fixed-effects) logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,608}
{txt}{col 57}{lalign 13:Wald chi2({res:5})}{col 70} = {res}{ralign 6:25.33}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0001}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-493.10469}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0351}

{txt}{ralign 82:(Std. err. adjusted for {res:122} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2}  .513201{col 30}{space 2} .2215772{col 41}{space 1}    2.32{col 50}{space 3}0.021{col 58}{space 4} .0789176{col 71}{space 3} .9474844
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0564534{col 30}{space 2} .0565903{col 41}{space 1}   -1.00{col 50}{space 3}0.318{col 58}{space 4}-.1673682{col 71}{space 3} .0544615
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .2264593{col 30}{space 2}   .31427{col 41}{space 1}    0.72{col 50}{space 3}0.471{col 58}{space 4}-.3894986{col 71}{space 3} .8424172
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.1569537{col 30}{space 2} .7630549{col 41}{space 1}   -0.21{col 50}{space 3}0.837{col 58}{space 4}-1.652514{col 71}{space 3} 1.338606
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-1.019261{col 30}{space 2} .5940351{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-2.183548{col 71}{space 3} .1450266
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

note: {bf:ilegal} omitted because of collinearity.
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-628.23498}  
Iteration 1:{space 3}log pseudolikelihood = {res:-589.65439}  
Iteration 2:{space 3}log pseudolikelihood = {res:-577.47349}  
Iteration 3:{space 3}log pseudolikelihood = {res: -577.4602}  
Iteration 4:{space 3}log pseudolikelihood = {res: -577.4602}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:3,013}
{txt}{col 57}{lalign 13:Wald chi2({res:10})}{col 70} = {res}{ralign 6:83.55}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 9:-577.4602}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0808}

{txt}{ralign 82:(Std. err. adjusted for {res:485} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .5417648{col 30}{space 2} .2302058{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0905697{col 71}{space 3} .9929599
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .1791083{col 30}{space 2} .3182881{col 41}{space 1}    0.56{col 50}{space 3}0.574{col 58}{space 4}-.4447249{col 71}{space 3} .8029414
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .1261563{col 30}{space 2} .5084045{col 41}{space 1}    0.25{col 50}{space 3}0.804{col 58}{space 4}-.8702983{col 71}{space 3} 1.122611
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.1420701{col 30}{space 2} .1107976{col 41}{space 1}   -1.28{col 50}{space 3}0.200{col 58}{space 4}-.3592295{col 71}{space 3} .0750892
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .3291279{col 30}{space 2} .2451669{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.1513904{col 71}{space 3} .8096462
{txt}{space 10}center {c |}{col 18}{res}{space 2} .4740559{col 30}{space 2} .2713438{col 41}{space 1}    1.75{col 50}{space 3}0.081{col 58}{space 4}-.0577682{col 71}{space 3}  1.00588
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0178443{col 30}{space 2} .0166028{col 41}{space 1}    1.07{col 50}{space 3}0.282{col 58}{space 4}-.0146966{col 71}{space 3} .0503852
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .7832982{col 30}{space 2} .0962514{col 41}{space 1}    8.14{col 50}{space 3}0.000{col 58}{space 4} .5946489{col 71}{space 3} .9719475
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .5949399{col 30}{space 2} 1.039307{col 41}{space 1}    0.57{col 50}{space 3}0.567{col 58}{space 4}-1.442065{col 71}{space 3} 2.631944
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.3281657{col 30}{space 2} .3834956{col 41}{space 1}   -0.86{col 50}{space 3}0.392{col 58}{space 4}-1.079803{col 71}{space 3} .4234717
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.964722{col 30}{space 2} .5202381{col 41}{space 1}   -9.54{col 50}{space 3}0.000{col 58}{space 4} -5.98437{col 71}{space 3}-3.945074
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
note: multiple positive outcomes within groups encountered.
note: 414 groups (1,951 obs) omitted because of all positive or
      all negative outcomes.
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-293.90957}  
Iteration 1:{space 3}log pseudolikelihood = {res:-292.81503}  
Iteration 2:{space 3}log pseudolikelihood = {res:-292.80678}  
Iteration 3:{space 3}log pseudolikelihood = {res:-292.80678}  
{res}
{txt}{col 1}Conditional (fixed-effects) logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,062}
{txt}{col 57}{lalign 13:Wald chi2({res:5})}{col 70} = {res}{ralign 6:39.18}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-292.80678}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0697}

{txt}{ralign 82:(Std. err. adjusted for {res:71} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .5251292{col 30}{space 2} .3035719{col 41}{space 1}    1.73{col 50}{space 3}0.084{col 58}{space 4}-.0698607{col 71}{space 3} 1.120119
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0358957{col 30}{space 2}  .070157{col 41}{space 1}   -0.51{col 50}{space 3}0.609{col 58}{space 4}-.1734008{col 71}{space 3} .1016094
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .5923306{col 30}{space 2} .4162057{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4}-.2234176{col 71}{space 3} 1.408079
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .4634365{col 30}{space 2} .7860864{col 41}{space 1}    0.59{col 50}{space 3}0.555{col 58}{space 4}-1.077265{col 71}{space 3} 2.004138
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-1.701359{col 30}{space 2} .9175181{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-3.499661{col 71}{space 3} .0969433
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
. 
. 
.         tex  Contract & `ub1_donate_15any' & `b1_donate_15any' & `db1_donate_15any' && `ub1_b5' & `b1_b5' & `db1_b5' && `ub1_b3' & `b1_b3' & `db1_b3' \\
{res}{txt}
{com}.         tex  \ \ \ \ p-value & `up_v_donate_15any' & `p_v_donate_15any' & `dp_v_donate_15any' && `up_v_b5' & `p_v_b5' & `dp_v_b5' && `up_v_b3' & `p_v_b3' & `dp_v_b3' \\ 
{res}{txt}
{com}.         tex  \ \ \ \ CI 95\% & [`ulci_donate_15any',`uuci_donate_15any']& [`lci_donate_15any',`uci_donate_15any'] & [`dlci_donate_15any',`duci_donate_15any'] && [`ulci_b5',`uuci_b5'] & [`lci_b5',`uci_b5'] & [`dlci_b5',`duci_b5'] && [`ulci_b3',`uuci_b3'] & [`lci_b3',`uci_b3'] & [`dlci_b3',`duci_b3'] \\ \hline
{res}{txt}
{com}.         tex  % & (`use1_donate_15any') & (`se1_donate_15any') & (`dse1_donate_15any') && (`use1_b5') & (`se1_b5') & (`dse1_b5') && (`use1_b3') & (`se1_b3') & (`dse1_b3') \\    
{res}{txt}
{com}.                 
.         
.         tex Observations & `uN_donate_15any' & `N_donate_15any' & `dN_donate_15any' && `uN_b5' & `N_b5' & `dN_b5' && `uN_b3' & `N_b3' & `dN_b3' \\
{res}{txt}
{com}.         tex Mean &  `mean_donate_15any' & `mean_donate_15any' &  `mean_donate_15any' && `mean_b5' & `mean_b5' &`mean_b5'&& `mean_b3' & `mean_b3' & `mean_b3' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `fem1_donate_15any' & `fem1_b5' & `fem1_b3' \\
.         tex log-likelihood & `ull_donate_15any' & `ll_donate_15any' & `dll_donate_15any' && `ull_b5' & `ll_b5' & `dll_b5' && `ull_b3' & `ll_b3' & `dll_b3' \\
{res}{txt}
{com}.         tex Controls mayor& no & yes & no && no & yes &no && no & yes & no \\
{res}{txt}
{com}.         tex Controls donor& no & yes & yes && no & yes &yes && no & yes & yes \\
{res}{txt}
{com}.         tex Municipality FE & no & no & yes &&no & no & yes && no & no & yes \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}150mm{c )-}{c -(}  \footnotesize{c -(}
{res}{txt}
{com}.         tex Estimates of the coefficient on receiving a contract in logit models of donating in the next election. Sample includes donors to the mayor. Columns 2 and 4 present conditional logit results with municipality as the grouping variable. Controls mayor denotes candidate's illegal registration of ID, being sanctioned, elected posts, ran as candidate past in elections, party has no clear ideological leaning, and non-family donations as a fraction of campaign revenue. Controls donor denotes logged value of donation, donated above legal limit, sanctioned, and donation rank among all donors. P-values and confidence intervals with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
.         
. ***********Marginal effects for text
. quietly: logit donate_15any contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}
{com}. margins, dydx(contract) at(sanc_before=.1581306  ilegal=0 p_prop=.589134 elec_exp=.6325224 pol_exp_d=.4663892 center=1 rank_don_alt_all=6.15589 lcont_donor_102=1.436941 contraloria=0)
{res}
{txt}{col 1}Average marginal effects{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:3,124}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(donate_15any), predict()}{p_end}
{p2col:dy/dx wrt:}{res:contract}{p_end}
{p2colreset}{...}
{lalign 4:At: }{space 0}{lalign 16:sanc_before} = {res:{ralign 8:.1581306}}
{lalign 4:}{space 0}{lalign 16:ilegal} = {res:{ralign 8:0}}
{lalign 4:}{space 0}{lalign 16:p_prop} = {res:{ralign 8:.589134}}
{lalign 4:}{space 0}{lalign 16:elec_exp} = {res:{ralign 8:.6325224}}
{lalign 4:}{space 0}{lalign 16:pol_exp_d} = {res:{ralign 8:.4663892}}
{lalign 4:}{space 0}{lalign 16:center} = {res:{ralign 8:1}}
{lalign 4:}{space 0}{lalign 16:rank_don_alt_all} = {res:{ralign 8:6.15589}}
{lalign 4:}{space 0}{lalign 16:lcont_donor_102} = {res:{ralign 8:1.436941}}
{lalign 4:}{space 0}{lalign 16:contraloria} = {res:{ralign 8:0}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}contract {c |}{col 14}{res}{space 2} .0412117{col 26}{space 2} .0133414{col 37}{space 1}    3.09{col 46}{space 3}0.002{col 54}{space 4} .0150631{col 67}{space 3} .0673603
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. quietly: logit b5 contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}
{com}. margins, dydx(contract) at(sanc_before=.1581306  ilegal=0 p_prop=.589134 elec_exp=.6325224 pol_exp_d=.4663892 center=1 rank_don_alt_all=6.15589 lcont_donor_102=1.436941 contraloria=0) 
{res}
{txt}{col 1}Average marginal effects{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:3,013}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(b5), predict()}{p_end}
{p2col:dy/dx wrt:}{res:contract}{p_end}
{p2colreset}{...}
{lalign 4:At: }{space 0}{lalign 16:sanc_before} = {res:{ralign 8:.1581306}}
{lalign 4:}{space 0}{lalign 16:ilegal} = {res:{ralign 8:0}}
{lalign 4:}{space 0}{lalign 16:p_prop} = {res:{ralign 8:.589134}}
{lalign 4:}{space 0}{lalign 16:elec_exp} = {res:{ralign 8:.6325224}}
{lalign 4:}{space 0}{lalign 16:pol_exp_d} = {res:{ralign 8:.4663892}}
{lalign 4:}{space 0}{lalign 16:center} = {res:{ralign 8:1}}
{lalign 4:}{space 0}{lalign 16:rank_don_alt_all} = {res:{ralign 8:6.15589}}
{lalign 4:}{space 0}{lalign 16:lcont_donor_102} = {res:{ralign 8:1.436941}}
{lalign 4:}{space 0}{lalign 16:contraloria} = {res:{ralign 8:0}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}contract {c |}{col 14}{res}{space 2} .0241984{col 26}{space 2} .0101531{col 37}{space 1}    2.38{col 46}{space 3}0.017{col 54}{space 4} .0042987{col 67}{space 3} .0440981
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableA4.do"
{txt}
{com}.         clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==2&family==0
{txt}(6,574 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(78 real changes made, 78 to missing)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableA4.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableA4.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableA4.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Contracts and next election donations (non-family donors to the runner-up){c )-}\label{c -(}tab:contracts_donation_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}lHcc c Hcc c HHH{c )-} \hline
{res}{txt}
{com}.         *tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Only mayor{c )-} \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} \cline{c -(}10-12{c )-}
.         tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} 
{res}{txt}
{com}.         tex & (1) & (1) & (2) && (4) & (3) & (4) && (7) & (5) & (6) \\ \hline
{res}{txt}
{com}.         tex & & & & & & & & & & &\\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  7{com}.                 
.                 local N_`x' : di %5.0f e(N)
{txt}  8{com}.                 local R2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.                 *T-statistics
.                 local t1_`x' = `b1_`x''/`se1_`x''
{txt} 18{com}.                 local t1_`x' : di %5.3f  `t1_`x''
{txt} 19{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 20{com}.                 scalar pval1_`x' = ttail(`df', abs(`t1_`x''))*2         
{txt} 21{com}. 
.                 
.         
.                 *Reg with FE
.                 areg `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 22{com}.                 
.                 local dN_`x' : di %5.0f e(N)
{txt} 23{com}.                 local dR2_`x' : di %5.3f e(r2)
{txt} 24{com}.                 
.                 matrix db = e(b)
{txt} 25{com}.                 matrix dv = e(V)
{txt} 26{com}.                 matrix dres=r(table)
{txt} 27{com}.                 
.                 local db1_`x' : di %5.3f db[1,1]
{txt} 28{com}.                 local dse1_`x' : di %5.3f sqrt(dv[1,1])
{txt} 29{com}.                 local dp_v_`x' :di %5.3f dres[4,1]
{txt} 30{com}.                 local duci_`x': di %5.3f dres[6,1]
{txt} 31{com}.                 local dlci_`x': di %5.3f dres[5,1]
{txt} 32{com}.                                 
.                 *T-statistics
.                 local dt1_`x' = `db1_`x''/`dse1_`x''
{txt} 33{com}.                 local dt1_`x' : di %5.3f  `dt1_`x''
{txt} 34{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 35{com}.                 scalar dpval1_`x' = ttail(`df', abs(`dt1_`x''))*2
{txt} 36{com}. 
.                 
. 
.                         
.         {c )-}       

{txt}Linear regression                               Number of obs     = {res}     1,917
                                                {txt}{help j_robustsingular:F(10, 376) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0143
                                                {txt}Root MSE          =    {res} .32055

{txt}{ralign 82:(Std. err. adjusted for {res:377} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2}-.0091319{col 30}{space 2} .0374821{col 41}{space 1}   -0.24{col 50}{space 3}0.808{col 58}{space 4}-.0828328{col 71}{space 3} .0645689
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} -.002174{col 30}{space 2}  .034208{col 41}{space 1}   -0.06{col 50}{space 3}0.949{col 58}{space 4}-.0694369{col 71}{space 3}  .065089
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1380942{col 30}{space 2} .0207476{col 41}{space 1}   -6.66{col 50}{space 3}0.000{col 58}{space 4}  -.17889{col 71}{space 3}-.0972983
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0620484{col 30}{space 2} .0388636{col 41}{space 1}   -1.60{col 50}{space 3}0.111{col 58}{space 4}-.1384656{col 71}{space 3} .0143688
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0114178{col 30}{space 2} .0130124{col 41}{space 1}   -0.88{col 50}{space 3}0.381{col 58}{space 4} -.037004{col 71}{space 3} .0141684
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0004509{col 30}{space 2} .0326949{col 41}{space 1}    0.01{col 50}{space 3}0.989{col 58}{space 4}-.0638369{col 71}{space 3} .0647386
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0017626{col 30}{space 2} .0220807{col 41}{space 1}    0.08{col 50}{space 3}0.936{col 58}{space 4}-.0416545{col 71}{space 3} .0451796
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0004171{col 30}{space 2} .0034946{col 41}{space 1}    0.12{col 50}{space 3}0.905{col 58}{space 4}-.0064543{col 71}{space 3} .0072885
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0454082{col 30}{space 2}  .025765{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0052533{col 71}{space 3} .0960697
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0454959{col 30}{space 2} .0807713{col 41}{space 1}   -0.56{col 50}{space 3}0.574{col 58}{space 4}-.2043159{col 71}{space 3} .1133241
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0452736{col 30}{space 2} .0408901{col 41}{space 1}   -1.11{col 50}{space 3}0.269{col 58}{space 4}-.1256755{col 71}{space 3} .0351283
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0918162{col 30}{space 2} .0583863{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0229884{col 71}{space 3} .2066208
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,917}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:377}
{txt}{col 53}{lalign 17:F({res:5}, {res:376})}{col 70} = {res}{ralign 6:4.08}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0013}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2892}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1128}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.3032}

{txt}{ralign 82:(Std. err. adjusted for {res:377} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0107559{col 30}{space 2} .0373435{col 41}{space 1}    0.29{col 50}{space 3}0.773{col 58}{space 4}-.0626724{col 71}{space 3} .0841842
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} -.006135{col 30}{space 2} .0046732{col 41}{space 1}   -1.31{col 50}{space 3}0.190{col 58}{space 4}-.0153239{col 71}{space 3}  .003054
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0454526{col 30}{space 2} .0374619{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4}-.0282085{col 71}{space 3} .1191137
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.1404087{col 30}{space 2} .1219355{col 41}{space 1}   -1.15{col 50}{space 3}0.250{col 58}{space 4}-.3801696{col 71}{space 3} .0993522
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0742181{col 30}{space 2} .0759749{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-.2236069{col 71}{space 3} .0751708
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0862349{col 30}{space 2}  .078387{col 41}{space 1}    1.10{col 50}{space 3}0.272{col 58}{space 4} -.067897{col 71}{space 3} .2403668
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,840
                                                {txt}{help j_robustsingular:F(10, 367) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0249
                                                {txt}Root MSE          =    {res} .26943

{txt}{ralign 82:(Std. err. adjusted for {res:368} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2}  .008281{col 30}{space 2} .0352389{col 41}{space 1}    0.23{col 50}{space 3}0.814{col 58}{space 4}-.0610144{col 71}{space 3} .0775765
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0137704{col 30}{space 2} .0304221{col 41}{space 1}   -0.45{col 50}{space 3}0.651{col 58}{space 4}-.0735938{col 71}{space 3}  .046053
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1022435{col 30}{space 2} .0190194{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}-.1396442{col 71}{space 3}-.0648428
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0789494{col 30}{space 2}  .033875{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-.1455628{col 71}{space 3} -.012336
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0069161{col 30}{space 2} .0116027{col 41}{space 1}   -0.60{col 50}{space 3}0.551{col 58}{space 4}-.0297322{col 71}{space 3} .0159001
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} -.012324{col 30}{space 2} .0292181{col 41}{space 1}   -0.42{col 50}{space 3}0.673{col 58}{space 4}-.0697798{col 71}{space 3} .0451319
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0117693{col 30}{space 2} .0202887{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0281273{col 71}{space 3} .0516659
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0026264{col 30}{space 2} .0032298{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4}-.0037249{col 71}{space 3} .0089777
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0546453{col 30}{space 2} .0253374{col 41}{space 1}    2.16{col 50}{space 3}0.032{col 58}{space 4} .0048206{col 71}{space 3}   .10447
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0074128{col 30}{space 2} .0818142{col 41}{space 1}   -0.09{col 50}{space 3}0.928{col 58}{space 4}-.1682963{col 71}{space 3} .1534706
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0337216{col 30}{space 2} .0389439{col 41}{space 1}   -0.87{col 50}{space 3}0.387{col 58}{space 4}-.1103029{col 71}{space 3} .0428597
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0330823{col 30}{space 2} .0544437{col 41}{space 1}    0.61{col 50}{space 3}0.544{col 58}{space 4}-.0739784{col 71}{space 3}  .140143
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,840}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:368}
{txt}{col 53}{lalign 17:F({res:5}, {res:367})}{col 70} = {res}{ralign 6:3.60}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0034}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.3075}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1319}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2535}

{txt}{ralign 82:(Std. err. adjusted for {res:368} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0102857{col 30}{space 2} .0365687{col 41}{space 1}    0.28{col 50}{space 3}0.779{col 58}{space 4}-.0616248{col 71}{space 3} .0821961
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0018044{col 30}{space 2} .0047315{col 41}{space 1}   -0.38{col 50}{space 3}0.703{col 58}{space 4}-.0111087{col 71}{space 3} .0074998
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0625269{col 30}{space 2} .0395182{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4}-.0151836{col 71}{space 3} .1402375
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0763719{col 30}{space 2} .1130759{col 41}{space 1}   -0.68{col 50}{space 3}0.500{col 58}{space 4}-.2987298{col 71}{space 3}  .145986
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0001581{col 30}{space 2} .0580895{col 41}{space 1}    0.00{col 50}{space 3}0.998{col 58}{space 4}-.1140719{col 71}{space 3} .1143881
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0061517{col 30}{space 2} .0825965{col 41}{space 1}   -0.07{col 50}{space 3}0.941{col 58}{space 4}-.1685736{col 71}{space 3} .1562702
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         tex  Contract & `ub1_donate_15any' & `b1_donate_15any' & `db1_donate_15any' && `ub1_b5' & `b1_b5' & `db1_b5' && `ub1_b3' & `b1_b3' & `db1_b3' \\
{res}{txt}
{com}.         tex  \ \ \ \ p-value & `up_v_donate_15any' & `p_v_donate_15any' & `dp_v_donate_15any' && `up_v_b5' & `p_v_b5' & `dp_v_b5' && `up_v_b3' & `p_v_b3' & `dp_v_b3' \\ 
{res}{txt}
{com}.         tex  \ \ \ \ CI 95\% & [`ulci_donate_15any',`uuci_donate_15any']& [`lci_donate_15any',`uci_donate_15any'] & [`dlci_donate_15any',`duci_donate_15any'] && [`ulci_b5',`uuci_b5'] & [`lci_b5',`uci_b5'] & [`dlci_b5',`duci_b5'] && [`ulci_b3',`uuci_b3'] & [`lci_b3',`uci_b3'] & [`dlci_b3',`duci_b3'] \\ \hline
{res}{txt}
{com}.         tex  % & (`use1_donate_15any') & (`se1_donate_15any') & (`dse1_donate_15any') && (`use1_b5') & (`se1_b5') & (`dse1_b5') && (`use1_b3') & (`se1_b3') & (`dse1_b3') \\    
{res}{txt}
{com}.         
.         tex Observations & `uN_donate_15any' & `N_donate_15any' & `dN_donate_15any' && `uN_b5' & `N_b5' & `dN_b5' && `uN_b3' & `N_b3' & `dN_b3' \\
{res}{txt}
{com}.         tex Mean &  `mean_donate_15any' & `mean_donate_15any' &  `mean_donate_15any' && `mean_b5' & `mean_b5' &`mean_b5'&& `mean_b3' & `mean_b3' & `mean_b3' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `fem1_donate_15any' & `fem1_b5' & `fem1_b3' \\
.         tex Controls mayor& no & yes & no && no & yes &no && no & yes & no \\
{res}{txt}
{com}.         tex Controls donor& no & yes & yes && no & yes &yes && no & yes & yes \\
{res}{txt}
{com}.         tex Municipality FE & no & no & yes &&no & no & yes && no & no & yes \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}150mm{c )-}{c -(}  \footnotesize{c -(}
{res}{txt}
{com}.         tex OLS estimates of the effect of receiving a contract on donating in the next election. Sample includes donors to the runner up. `Controls mayor' denotes candidate's illegal registration of ID, being sanctioned, elected posts, ran as candidate in past elections, party has no clear ideological leaning, and non-family donations as a fraction of campaign revenue. `Controls donor' denotes logged value of donation, donated above legal limit, sanctioned, and rank of donation among all donors. P-values and confidence intervals with clusters at the municipality level. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableA5.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==1&family==0
{txt}(5,397 observations deleted)

{com}. keep if b2==0&b4==0
{txt}(175 observations deleted)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableA5.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableA5.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableA5.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Contracts and next mayoral election donations (non-family){c )-}\label{c -(}tab:contracts_donation_mayors{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}lHHH H HHH H Hcc{c )-} \hline
{res}{txt}
{com}.         *tex Outcome: & \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Any race{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor{c )-} && \multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Only mayor{c )-} \\ \cline{c -(}2-4{c )-} \cline{c -(}6-8{c )-} \cline{c -(}10-12{c )-}
. tex Outcome & &&&& && &&\multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Mayor only{c )-} \\  \cline{c -(}11-12{c )-}
{res}{txt}
{com}.         tex & (1) & (1) & (2) && (4) & (3) & (4) && (7) & (1) & (2) \\ \hline
{res}{txt}
{com}.         tex & & & & & & & & & & &\\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in b3{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim , vce(cluster muni_code)
{txt}  7{com}.                 
.                 local N_`x' : di %5.0f e(N)
{txt}  8{com}.                 local R2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.                 *T-statistics
.                 local t1_`x' = `b1_`x''/`se1_`x''
{txt} 18{com}.                 local t1_`x' : di %5.3f  `t1_`x''
{txt} 19{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 20{com}.                 scalar pval1_`x' = ttail(`df', abs(`t1_`x''))*2         
{txt} 21{com}. 
.                 
.                 
.                 *Reg with FE
.                 areg `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 22{com}.                 
.                 local dN_`x' : di %5.0f e(N)
{txt} 23{com}.                 local dR2_`x' : di %5.3f e(r2)
{txt} 24{com}.                 
.                 matrix db = e(b)
{txt} 25{com}.                 matrix dv = e(V)
{txt} 26{com}.                 matrix dres=r(table)
{txt} 27{com}.                 
.                 local db1_`x' : di %5.3f db[1,1]
{txt} 28{com}.                 local dse1_`x' : di %5.3f sqrt(dv[1,1])
{txt} 29{com}.                 local dp_v_`x' :di %5.3f dres[4,1]
{txt} 30{com}.                 local duci_`x': di %5.3f dres[6,1]
{txt} 31{com}.                 local dlci_`x': di %5.3f dres[5,1]
{txt} 32{com}.                                 
.                 *T-statistics
.                 local dt1_`x' = `db1_`x''/`dse1_`x''
{txt} 33{com}.                 local dt1_`x' : di %5.3f  `dt1_`x''
{txt} 34{com}.                 
.                 
.                 *P-values
.                 local df : di `e(N)'-`e(k_absorb)'-`e(df_m)'-1
{txt} 35{com}.                 scalar dpval1_`x' = ttail(`df', abs(`dt1_`x''))*2
{txt} 36{com}. 
. 
.                         
.         {c )-}       
{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res}     2,952
                                                {txt}F(10, 480)        =  {res}     4.47
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0140
                                                {txt}Root MSE          =    {res} .17997

{txt}{ralign 82:(Std. err. adjusted for {res:481} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b3{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0198155{col 30}{space 2} .0123207{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0043936{col 71}{space 3} .0440246
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0027093{col 30}{space 2} .0146334{col 41}{space 1}    0.19{col 50}{space 3}0.853{col 58}{space 4}-.0260441{col 71}{space 3} .0314626
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .0228234{col 30}{space 2} .0180467{col 41}{space 1}    1.26{col 50}{space 3}0.207{col 58}{space 4}-.0126369{col 71}{space 3} .0582838
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0042122{col 30}{space 2} .0044505{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.0129571{col 71}{space 3} .0045326
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0114634{col 30}{space 2} .0101242{col 41}{space 1}    1.13{col 50}{space 3}0.258{col 58}{space 4}-.0084298{col 71}{space 3} .0313566
{txt}{space 10}center {c |}{col 18}{res}{space 2}  .010266{col 30}{space 2} .0077885{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.0050378{col 71}{space 3} .0255699
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0005817{col 30}{space 2} .0006967{col 41}{space 1}   -0.83{col 50}{space 3}0.404{col 58}{space 4}-.0019507{col 71}{space 3} .0007873
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}  .018097{col 30}{space 2} .0057955{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .0067093{col 71}{space 3} .0294847
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0257459{col 30}{space 2} .0058984{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.0373358{col 71}{space 3}-.0141559
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0081247{col 30}{space 2} .0233714{col 41}{space 1}    0.35{col 50}{space 3}0.728{col 58}{space 4}-.0377982{col 71}{space 3} .0540475
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0151632{col 30}{space 2} .0158114{col 41}{space 1}   -0.96{col 50}{space 3}0.338{col 58}{space 4}-.0462314{col 71}{space 3}  .015905
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:2,952}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:481}
{txt}{col 53}{lalign 17:F({res:5}, {res:480})}{col 70} = {res}{ralign 6:3.04}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0103}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2277}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0758}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.1739}

{txt}{ralign 82:(Std. err. adjusted for {res:481} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b3{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}contract {c |}{col 18}{res}{space 2} .0181355{col 30}{space 2} .0136045{col 41}{space 1}    1.33{col 50}{space 3}0.183{col 58}{space 4}-.0085963{col 71}{space 3} .0448673
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0002221{col 30}{space 2} .0015944{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4} -.003355{col 71}{space 3} .0029108
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0270987{col 30}{space 2} .0116011{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0043034{col 71}{space 3}  .049894
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0081901{col 30}{space 2} .0111696{col 41}{space 1}   -0.73{col 50}{space 3}0.464{col 58}{space 4}-.0301373{col 71}{space 3} .0137572
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.072216{col 30}{space 2} .0382352{col 41}{space 1}   -1.89{col 50}{space 3}0.060{col 58}{space 4} -.147345{col 71}{space 3}  .002913
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0024987{col 30}{space 2}  .024066{col 41}{space 1}   -0.10{col 50}{space 3}0.917{col 58}{space 4}-.0497865{col 71}{space 3} .0447891
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
. 
.         tex  Contract & `ub1_donate_15any' & `b1_donate_15any' & `db1_donate_15any' && `ub1_b5' & `b1_b5' & `db1_b5' && `ub1_b3' & `b1_b3' & `db1_b3' \\
{res}{txt}
{com}.         tex  \ \ \ \ p-value & `up_v_donate_15any' & `p_v_donate_15any' & `dp_v_donate_15any' && `up_v_b5' & `p_v_b5' & `dp_v_b5' && `up_v_b3' & `p_v_b3' & `dp_v_b3' \\ 
{res}{txt}
{com}.         tex  \ \ \ \ CI 95\% & [`ulci_donate_15any',`uuci_donate_15any']& [`lci_donate_15any',`uci_donate_15any'] & [`dlci_donate_15any',`duci_donate_15any'] && [`ulci_b5',`uuci_b5'] & [`lci_b5',`uci_b5'] & [`dlci_b5',`duci_b5'] && [`ulci_b3',`uuci_b3'] & [`lci_b3',`uci_b3'] & [`dlci_b3',`duci_b3'] \\ \hline
{res}{txt}
{com}.         tex  % & (`use1_donate_15any') & (`se1_donate_15any') & (`dse1_donate_15any') && (`use1_b5') & (`se1_b5') & (`dse1_b5') && (`use1_b3') & (`se1_b3') & (`dse1_b3') \\    
{res}{txt}
{com}.         
.         tex Observations & `uN_donate_15any' & `N_donate_15any' & `dN_donate_15any' && `uN_b5' & `N_b5' & `dN_b5' && `uN_b3' & `N_b3' & `dN_b3' \\
{res}{txt}
{com}.         tex Mean &  `mean_donate_15any' & `mean_donate_15any' &  `mean_donate_15any' && `mean_b5' & `mean_b5' &`mean_b5'&& `mean_b3' & `mean_b3' & `mean_b3' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `fem1_donate_15any' & `fem1_b5' & `fem1_b3' \\
.         tex R-squared & `uR2_donate_15any' & `R2_donate_15any' & `dR2_donate_15any' && `uR2_b5' & `R2_b5' & `dR2_b5' && `uR2_b3' & `R2_b3' & `dR2_b3' \\
{res}{txt}
{com}.         tex Controls mayor& no & yes & no && no & yes &no && no & yes & no \\
{res}{txt}
{com}.         tex Controls donor& no & yes & yes && no & yes &yes && no & yes & yes \\
{res}{txt}
{com}.         tex Municipality FE & no & no & yes &&no & no & yes && no & no & yes \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}150mm{c )-}{c -(}  \footnotesize{c -(}
{res}{txt}
{com}.         tex OLS estimates of the effect of receiving a contract on donating exclusively to the next mayoral election. Sample includes donors to the mayor. Controls mayor include:  candidate's illegal registration of ID, being sanctioned, elected posts, ran as candidate in past elections, party has no clear ideological leaning, and non-family donations as a fraction of campaign revenue. Controls donor include: logged value of donation, donated above legal limit, sanctioned, and rank of donation among all donors. P-values and confidence intervals with clusters at the municipality level. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableB1.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==1&family==0
{txt}(5,397 observations deleted)

{com}.         
.         replace b5=. if b2!=0
{txt}(113 real changes made, 113 to missing)

{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Regressions
.                 quietly: reg `x' contract sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim i.muni_code, vce(cluster muni_code)
{txt}  3{com}.                 sensemakr `x' contract rank_don_alt_all lcont_donor_102 contraloria above_lim i.muni_code if e(sample), treat(contract) benchmark(lcont_donor_102) 
{txt}  4{com}. 
.                         
.         {c )-}       
{res}
{space 59}{txt} DOF    =    2631 
{space 59} q      =    1.00 
{space 59} alpha  =    0.05 
{space 59} reduce =    TRUE
{space 59} H0     =       0
{res}
{txt} Treatment{space 5} {c |} {space 4}Coef.{space 5} S.E.{space 6}t(H0){space 4}R2yd.x{space 5}RV_q{space 4}RV_qa
{res}{hline 16}{c +}{hline 59}
{txt}       contract {c |}  {res}  0.0436    0.0162     2.6892    0.0027   0.0511   0.0141

{txt} Partial R2 of the treatment with the outcome (R2yd.x): 
 An extreme confounder (orthogonal to the covariates) that explains 100 percent of the 
 residual variance of the outcome, would need to explain at least 0.27 percent of the 
 residual variance of the treatment to fully account for the observed estimated effect. 
 
{res}{txt} Robustness Value, q = 1.00 (RV_q): 
 Unobserved confounders (orthogonal to the covariates) that explain more than 5.11 percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the point estimate to 0 (a bias of 100 percent of the original estimate). Conversely, 
 unobserved confounders that do not explain more than 5.11 percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the point estimate 
 to 0. 
 
{res}{txt} Robustness Value, q = 1.00, alpha = 0.05 (RV_qa): 
 Unobserved confounders (orthogonal to the covariates) that explain more than 1.41 percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the estimate to a range where it is no longer 'statistically different' from 0 (a bias 
 of 100 percent of the original estimate), at the significance level of alpha = 0.05. Conversely,
 unobserved confounders that do not explain more than 1.41 percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the estimate to a 
 range where it is no longer 'statistically different' from 0, at the significance 
 level of alpha = 0.05 
 
{res}{txt} Bounds on Omitted Variable Bias: 
{res}{txt} The table shows the maximum strength of unobserved confounders, bounded by a multiple of the 
 observed explanatory power of the chosen benchmark covariate(s) with the treatment and the outcome.

{res}{txt} Bound {space 16}{c |}{space 3}R2dz.x{space 3}R2yz.dx{space 5}Coef.{space 6}S.E.{space 5}t(H0){space 2}Lower CI{space 1}Upper CI 
{hline 23}{c +}{hline 70}
{res}{txt} 1.00x lcont_donor_102 {c |}{res}   0.0016    0.0006    0.0428    0.0162    2.6391    0.0110   0.0746 
{txt} 2.00x lcont_donor_102 {c |}{res}   0.0031    0.0011    0.0420    0.0162    2.5896    0.0102   0.0738 
{txt} 3.00x lcont_donor_102 {c |}{res}   0.0047    0.0017    0.0412    0.0162    2.5400    0.0094   0.0731 


{txt} Extreme Bound{space 9}{c |}{space 3}R2dz.x{space 3}R2yz.dx{space 5}Coef.
{hline 23}{c +}{hline 30} 
{res}{txt} 1.00x lcont_donor_102 {c |}{res}   0.0016{space 2}  1.0000{space 2}  0.0107 
{txt} 2.00x lcont_donor_102 {c |}{res}   0.0031{space 2}  1.0000{space 2} -0.0029 
{txt} 3.00x lcont_donor_102 {c |}{res}   0.0047{space 2}  1.0000{space 2} -0.0134 

{space 59}{txt} DOF    =    2523 
{space 59} q      =    1.00 
{space 59} alpha  =    0.05 
{space 59} reduce =    TRUE
{space 59} H0     =       0
{res}
{txt} Treatment{space 5} {c |} {space 4}Coef.{space 5} S.E.{space 6}t(H0){space 4}R2yd.x{space 5}RV_q{space 4}RV_qa
{res}{hline 16}{c +}{hline 59}
{txt}       contract {c |}  {res}  0.0269    0.0131     2.0523    0.0017   0.0400   0.0018

{txt} Partial R2 of the treatment with the outcome (R2yd.x): 
 An extreme confounder (orthogonal to the covariates) that explains 100 percent of the 
 residual variance of the outcome, would need to explain at least 0.17 percent of the 
 residual variance of the treatment to fully account for the observed estimated effect. 
 
{res}{txt} Robustness Value, q = 1.00 (RV_q): 
 Unobserved confounders (orthogonal to the covariates) that explain more than 4.00 percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the point estimate to 0 (a bias of 100 percent of the original estimate). Conversely, 
 unobserved confounders that do not explain more than 4.00 percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the point estimate 
 to 0. 
 
{res}{txt} Robustness Value, q = 1.00, alpha = 0.05 (RV_qa): 
 Unobserved confounders (orthogonal to the covariates) that explain more than 0.18 percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the estimate to a range where it is no longer 'statistically different' from 0 (a bias 
 of 100 percent of the original estimate), at the significance level of alpha = 0.05. Conversely,
 unobserved confounders that do not explain more than 0.18 percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the estimate to a 
 range where it is no longer 'statistically different' from 0, at the significance 
 level of alpha = 0.05 
 
{res}{txt} Bounds on Omitted Variable Bias: 
{res}{txt} The table shows the maximum strength of unobserved confounders, bounded by a multiple of the 
 observed explanatory power of the chosen benchmark covariate(s) with the treatment and the outcome.

{res}{txt} Bound {space 16}{c |}{space 3}R2dz.x{space 3}R2yz.dx{space 5}Coef.{space 6}S.E.{space 5}t(H0){space 2}Lower CI{space 1}Upper CI 
{hline 23}{c +}{hline 70}
{res}{txt} 1.00x lcont_donor_102 {c |}{res}   0.0011    0.0018    0.0260    0.0131    1.9810    0.0003   0.0517 
{txt} 2.00x lcont_donor_102 {c |}{res}   0.0022    0.0037    0.0251    0.0131    1.9100   -0.0007   0.0508 
{txt} 3.00x lcont_donor_102 {c |}{res}   0.0033    0.0055    0.0241    0.0131    1.8389   -0.0016   0.0498 


{txt} Extreme Bound{space 9}{c |}{space 3}R2dz.x{space 3}R2yz.dx{space 5}Coef.
{hline 23}{c +}{hline 30} 
{res}{txt} 1.00x lcont_donor_102 {c |}{res}   0.0011{space 2}  1.0000{space 2}  0.0050 
{txt} 2.00x lcont_donor_102 {c |}{res}   0.0022{space 2}  1.0000{space 2} -0.0042 
{txt} 3.00x lcont_donor_102 {c |}{res}   0.0033{space 2}  1.0000{space 2} -0.0112 
{txt}
{com}. 
.         
. 
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableC1.do"
{txt}
{com}. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use  "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
.         global balance_ind women age black indi_bkg leftist rightwing sanc_before ilegal pol_exp_d elec_exp_d all 
{txt}
{com}.         global balance_fin all total_income donations_total 
{txt}
{com}.         global balance_donors family cont_donor_102 cont_donor_101 contraloria above_lim    
{txt}
{com}.         global balance_all $balance_ind $balance_fin $balance_donors
{txt}
{com}. 
. 
.         
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableC1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableC1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableC1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Candidate characteristics around the electoral victory cutoff{c )-}\label{c -(}tab:smooth_win{c )-}
{res}{txt}
{com}.         tex \begin{c -(}center{c )-}
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}%
{res}{txt}
{com}.         tex {c -(}\normalsize
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c c c{c )-}
{res}{txt}
{com}.         tex \toprule[1.5pt]
{res}{txt}
{com}.         tex \multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}{c )-} & Mean &  Std. Dev. & Victory & CI 95\% &
{res}{txt}
{com}.         tex Obs. & Band. Obs.  & Bandwith & p-value \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8) \\
{res}{txt}
{com}.         tex \hline
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel A:Candidates' characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         
.         foreach x in $balance_all{c -(}      
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 sum `x' if margin_victory!=.
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' margin_victory if (rank==1 | rank==2), all vce(cluster muni_code) 
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %9.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_cl)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval1_`x' : di %5.3f `e(pv_cl)'
{txt} 18{com}.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 19{com}.                 
.                 
.         {c )-}       

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}women {c |}{res}      1,150    .1165217    .3209891          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      262{col 34}      301{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.573{col 34}    0.573
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      387{col 34}      451

Outcome: women. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01831{col 33} .06314{col 43}0.2900{col 52}0.772{col 60}-.105444{col 73} .142066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03817{col 33} .06314{col 43}0.6045{col 52}0.546{col 60}-.085587{col 73} .161923
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03817{col 33} .07318{col 43}0.5216{col 52}0.602{col 60}-.105258{col 73} .181594
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}age {c |}{res}      1,047    44.90831    9.710494         18         76

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1047
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      468{col 34}      579{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      293{col 34}      349{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.086{col 34}    0.086
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.137{col 34}    0.137
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.629{col 34}    0.629
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      380{col 34}      457

Outcome: age. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .28482{col 33} 1.6111{col 43}0.1768{col 52}0.860{col 60}-2.87278{col 73} 3.44243
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .32022{col 33} 1.6111{col 43}0.1988{col 52}0.842{col 60}-2.83739{col 73} 3.47782
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .32022{col 33} 1.9087{col 43}0.1678{col 52}0.867{col 60}-3.42083{col 73} 4.06126
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}black {c |}{res}      1,047    .0515759     .221275          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1047
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      468{col 34}      579{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      307{col 34}      367{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.096{col 34}    0.096
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.156{col 34}    0.156
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.616{col 34}    0.616
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      416{col 34}      495

Outcome: black. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00905{col 33} .03658{col 43}0.2475{col 52}0.805{col 60} -.06264{col 73} .080743
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01453{col 33} .03658{col 43}0.3972{col 52}0.691{col 60}-.057164{col 73} .086219
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01453{col 33} .04231{col 43}0.3434{col 52}0.731{col 60}-.068398{col 73} .097453
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}indi_bkg {c |}{res}      1,047    .1241643    .3299265          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1047
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      468{col 34}      579{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      247{col 34}      282{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.589{col 34}    0.589
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      344{col 34}      407

Outcome: indi_bkg. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04139{col 33}   .063{col 43}-0.6570{col 52}0.511{col 60} -.16488{col 73} .082093
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05771{col 33}   .063{col 43}-0.9159{col 52}0.360{col 60}-.181193{col 73}  .06578
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05771{col 33} .07342{col 43}-0.7860{col 52}0.432{col 60}-.201604{col 73}  .08619
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}leftist {c |}{res}      1,150    .0286957    .1670224          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      274{col 34}      313{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.580{col 34}    0.580
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      393{col 34}      457

Outcome: leftist. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03607{col 33} .03735{col 43}-0.9657{col 52}0.334{col 60}-.109273{col 73} .037135
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0479{col 33} .03735{col 43}-1.2825{col 52}0.200{col 60}-.121104{col 73} .025304
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0479{col 33} .04334{col 43}-1.1053{col 52}0.269{col 60}-.132837{col 73} .037037
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}rightwing {c |}{res}      1,150     .246087    .4309172          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      276{col 34}      316{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.132{col 34}    0.132
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      414{col 34}      494

Outcome: rightwing. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.12484{col 33} .07447{col 43}-1.6764{col 52}0.094{col 60} -.27079{col 73}  .02112
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15156{col 33} .07447{col 43}-2.0353{col 52}0.042{col 60}-.297519{col 73}-.005609
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15156{col 33} .08392{col 43}-1.8060{col 52}0.071{col 60}-.316049{col 73} .012921
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}sanc_before {c |}{res}      1,150    .1069565    .3091924          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      276{col 34}      316{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.647{col 34}    0.647
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      360{col 34}      427

Outcome: sanc_before. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05258{col 33} .05757{col 43}-0.9133{col 52}0.361{col 60}-.165412{col 73} .060256
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04915{col 33} .05757{col 43}-0.8538{col 52}0.393{col 60}-.161984{col 73} .063684
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04915{col 33} .06823{col 43}-0.7203{col 52}0.471{col 60}-.182883{col 73} .084583
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}ilegal {c |}{res}      1,150    .0034783    .0588997          0          1
{err}Not enough variability to compute the preliminary bandwidth. Try checking for mass points with option {cmd:masspoints(check)}.
{err}Not enough variability to compute the bias bandwidth (b). Try checking for mass points with option {cmd:masspoints(check)}. 
{err}Not enough variability to compute the loc. poly. bandwidth (h). Try checking for mass points with option {cmd:masspoints(check)}.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      298{col 34}      343{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.075{col 34}    0.075
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.650{col 34}    0.650
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      385{col 34}      449

Outcome: ilegal. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01804{col 33} .01646{col 43}-1.0958{col 52}0.273{col 60}-.050302{col 73} .014225
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02129{col 33} .01646{col 43}-1.2932{col 52}0.196{col 60}-.053551{col 73} .010977
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02129{col 33} .02054{col 43}-1.0362{col 52}0.300{col 60}-.061553{col 73} .018979
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}pol_exp_d {c |}{res}      1,148    .4407666    .4966954          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1148
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      517{col 34}      631{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      239{col 34}      268{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.539{col 34}    0.539
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      355{col 34}      420

Outcome: pol_exp_d. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00393{col 33} .09384{col 43}-0.0419{col 52}0.967{col 60}-.187866{col 73} .179997
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0396{col 33} .09384{col 43}-0.4220{col 52}0.673{col 60}-.223529{col 73} .144334
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0396{col 33} .10791{col 43}-0.3669{col 52}0.714{col 60}-.251104{col 73} .171909
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}elec_exp_d {c |}{res}      1,148    .3580139    .4796252          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1148
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      517{col 34}      631{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      293{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.065{col 34}    0.065
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.586{col 34}    0.586
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      371{col 34}      437

Outcome: elec_exp_d. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01554{col 33} .08678{col 43}0.1791{col 52}0.858{col 60}-.154543{col 73} .185622
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00764{col 33} .08678{col 43}-0.0880{col 52}0.930{col 60}-.177719{col 73} .162446
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00764{col 33} .10108{col 43}-0.0755{col 52}0.940{col 60}-.205759{col 73} .190486
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}all {c |}{res}      1,150    5.755652     8.58999          1         98

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      314{col 34}      366{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.126{col 34}    0.126
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.656{col 34}    0.656
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      408{col 34}      480

Outcome: all. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .46648{col 33} 1.3087{col 43}0.3564{col 52}0.722{col 60}-2.09861{col 73} 3.03157
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .65988{col 33} 1.3087{col 43}0.5042{col 52}0.614{col 60}-1.90521{col 73} 3.22497
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .65988{col 33} 1.5091{col 43}0.4373{col 52}0.662{col 60}-2.29782{col 73} 3.61757
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}all {c |}{res}      1,150    5.755652     8.58999          1         98

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      314{col 34}      366{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.126{col 34}    0.126
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.656{col 34}    0.656
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      408{col 34}      480

Outcome: all. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .46648{col 33} 1.3087{col 43}0.3564{col 52}0.722{col 60}-2.09861{col 73} 3.03157
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .65988{col 33} 1.3087{col 43}0.5042{col 52}0.614{col 60}-1.90521{col 73} 3.22497
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .65988{col 33} 1.5091{col 43}0.4373{col 52}0.662{col 60}-2.29782{col 73} 3.61757
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
total_income {c |}{res}      1,150    64.12248     128.786      .3056   1639.796

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      331{col 34}      386{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.090{col 34}    0.090
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.145{col 34}    0.145
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.617{col 34}    0.617
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      440{col 34}      518

Outcome: total_income. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} 15.288{col 33} 17.885{col 43}0.8548{col 52}0.393{col 60}-19.7662{col 73}  50.343
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} 16.898{col 33} 17.885{col 43}0.9448{col 52}0.345{col 60}-18.1569{col 73} 51.9522
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} 16.898{col 33} 20.715{col 43}0.8157{col 52}0.415{col 60}-23.7034{col 73} 57.4987
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
donations_~l {c |}{res}      1,150    .5829579     .274351   .0000476          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      250{col 34}      285{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.062{col 34}    0.062
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.603{col 34}    0.603
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      351{col 34}      416

Outcome: donations_total. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07768{col 33} .04905{col 43}-1.5835{col 52}0.113{col 60}-.173824{col 73} .018468
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08662{col 33} .04905{col 43}-1.7658{col 52}0.077{col 60}-.182768{col 73} .009524
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08662{col 33} .05833{col 43}-1.4851{col 52}0.138{col 60}-.200942{col 73} .027699
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}family {c |}{res}      1,150    .4364524     .412078          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      294{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.065{col 34}    0.065
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.584{col 34}    0.584
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      374{col 34}      439

Outcome: family. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00667{col 33}   .077{col 43}-0.0866{col 52}0.931{col 60}-.157576{col 73}  .14424
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02735{col 33}   .077{col 43}-0.3552{col 52}0.722{col 60}-.178255{col 73} .123561
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02735{col 33} .08979{col 43}-0.3046{col 52}0.761{col 60}-.203333{col 73} .148639
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~102 {c |}{res}        823    5.856738    8.061539         .1   132.7175

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      184{col 34}      205{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.600{col 34}    0.600
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      264{col 34}      310

Outcome: cont_donor_102. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -3.764{col 33}  2.628{col 43}-1.4323{col 52}0.152{col 60}-8.91468{col 73} 1.38671
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-4.4852{col 33}  2.628{col 43}-1.7067{col 52}0.088{col 60}-9.63587{col 73} .665524
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-4.4852{col 33} 3.1941{col 43}-1.4042{col 52}0.160{col 60}-10.7455{col 73} 1.77514
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~101 {c |}{res}        778    10.22866    12.36897      .0005        148

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      163{col 34}      195{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.060{col 34}    0.060
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.096{col 34}    0.096
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.631{col 34}    0.631
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      223{col 34}      283

Outcome: cont_donor_101. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.86229{col 33} 3.3303{col 43}-0.2589{col 52}0.796{col 60} -7.3896{col 73} 5.66502
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-1.9771{col 33} 3.3303{col 43}-0.5937{col 52}0.553{col 60}-8.50439{col 73} 4.55022
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-1.9771{col 33} 3.9493{col 43}-0.5006{col 52}0.617{col 60}-9.71755{col 73} 5.76338
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}contraloria {c |}{res}      1,150    .0059253    .0416042          0         .5

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      243{col 34}      271{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.662{col 34}    0.662
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      331{col 34}      385

Outcome: contraloria. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01061{col 33} .00623{col 43}-1.7050{col 52}0.088{col 60}-.022815{col 73} .001587
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01041{col 33} .00623{col 43}-1.6718{col 52}0.095{col 60}-.022608{col 73} .001794
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01041{col 33} .00701{col 43}-1.4846{col 52}0.138{col 60}-.024146{col 73} .003332
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}above_lim {c |}{res}      1,150     .267597    .3820391          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      226{col 34}      254{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.052{col 34}    0.052
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.101{col 34}    0.101
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.520{col 34}    0.520
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      346{col 34}      411

Outcome: above_lim. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13263{col 33} .07702{col 43}-1.7219{col 52}0.085{col 60}-.283592{col 73} .018333
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.16549{col 33} .07702{col 43}-2.1485{col 52}0.032{col 60}-.316449{col 73}-.014524
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.16549{col 33} .08771{col 43}-1.8866{col 52}0.059{col 60}-.337404{col 73} .006431
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

{com}. 
.         
.         
. 
.         
.         
.         *Table continue
.         tex \ Women & `mean_women' & `sd_women' & `beta2_women' & [`ser1_women',`ser2_women'] & `N_women' & `Neff_women' & `bw_women' & `pval2_women' \\
{res}{txt}
{com}.         tex \ Age & `mean_age' & `sd_age' & `beta2_age' & [`ser1_age',`ser2_age'] & `N_age' & `Neff_age' & `bw_age' & `pval2_age' \\
{res}{txt}
{com}.         tex \ Black & `mean_black' & `sd_black' & `beta2_black' & [`ser1_black',`ser2_black'] & `N_black' & `Neff_black' & `bw_black' & `pval2_black' \\
{res}{txt}
{com}.         tex \ Indigenous & `mean_indi_bkg' & `sd_indi_bkg' & `beta2_indi_bkg' & [`ser1_indi_bkg',`ser2_indi_bkg'] & `N_indi_bkg' & `Neff_indi_bkg' & `bw_indi_bkg' & `pval2_indi_bkg' \\
{res}{txt}
{com}.         tex \ Left wing & `mean_leftist' & `sd_leftist' & `beta2_leftist' & [`ser1_leftist',`ser2_leftist'] & `N_leftist' & `Neff_leftist' & `bw_leftist' & `pval2_leftist' \\
{res}{txt}
{com}.         tex \ Right wing & `mean_rightwing' & `sd_rightwing' & `beta2_rightwing' & [`ser1_rightwing',`ser2_rightwing'] & `N_rightwing' & `Neff_rightwing' & `bw_rightwing' & `pval2_rightwing' \\
{res}{txt}
{com}.         tex \ Sanctioned & `mean_sanc_before' & `sd_sanc_before' & `beta2_sanc_before' & [`ser1_sanc_before',`ser2_sanc_before'] & `N_sanc_before' & `Neff_sanc_before' & `bw_sanc_before' & `pval2_sanc_before' \\
{res}{txt}
{com}.         tex \ Illegal Registration of ID. & `mean_ilegal' & `sd_ilegal' & `beta2_ilegal' & [`ser1_ilegal',`ser2_ilegal'] & `N_ilegal' & `Neff_ilegal' & `bw_ilegal' & `pval2_ilegal' \\
{res}{txt}
{com}.         tex \ Political experience & `mean_pol_exp_d' & `sd_pol_exp_d' & `beta2_pol_exp_d' & [`ser1_pol_exp_d',`ser2_pol_exp_d'] & `N_pol_exp_d' & `Neff_pol_exp_d' & `bw_pol_exp_d' & `pval2_pol_exp_d' \\
{res}{txt}
{com}.         tex \ Held office before & `mean_elec_exp_d' & `sd_elec_exp_d' & `beta2_elec_exp_d' & [`ser1_elec_exp_d',`ser2_elec_exp_d'] & `N_elec_exp_d' & `Neff_elec_exp_d' & `bw_elec_exp_d' & `pval2_elec_exp_d' \\
{res}{txt}
{com}.         tex \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel B: General funding covariates{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Donors (all) & `mean_all' & `sd_all' & `beta2_all' & [`ser1_all',`ser2_all'] & `N_all' & `Neff_all' & `bw_all' & `pval2_all' \\
{res}{txt}
{com}.         tex \ Campaign revenue & `mean_total_income' & `sd_total_income' & `beta2_total_income' & [`ser1_total_income',`ser2_total_income'] & `N_total_income' & `Neff_total_income' & `bw_total_income' & `pval2_total_income' \\
{res}{txt}
{com}.         tex \ Donations /Revenue & `mean_donations_total' & `sd_donations_total' & `beta2_donations_total' & [`ser1_donations_total',`ser2_donations_total'] & `N_donations_total' & `Neff_donations_total' & `bw_donations_total' & `pval2_donations_total' \\
{res}{txt}
{com}. 
.         tex \\
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel C: Donors characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Family & `mean_family' & `sd_family' & `beta2_family' & [`ser1_family',`ser2_family'] & `N_family' & `Neff_family' & `bw_family' & `pval2_family' \\
{res}{txt}
{com}.         tex \ Avg. Donation (non-family) & `mean_cont_donor_102' & `sd_cont_donor_102' & `beta2_cont_donor_102' & [`ser1_cont_donor_102',`ser2_cont_donor_102'] & `N_cont_donor_102' & `Neff_cont_donor_102' & `bw_cont_donor_102' & `pval2_cont_donor_102' \\
{res}{txt}
{com}.         tex \ Avg. Donation (family) & `mean_cont_donor_101' & `sd_cont_donor_101' & `beta2_cont_donor_101' & [`ser1_cont_donor_101',`ser2_cont_donor_101'] & `N_cont_donor_101' & `Neff_cont_donor_101' & `bw_cont_donor_101' & `pval2_cont_donor_101' \\
{res}{txt}
{com}.         tex \ Comptroller sanction & `mean_contraloria' & `sd_contraloria' & `beta2_contraloria' & [`ser1_contraloria',`ser2_contraloria'] & `N_contraloria' & `Neff_contraloria' & `bw_contraloria' & `pval2_contraloria' \\
{res}{txt}
{com}.         tex \ Above limit & `mean_above_lim' & `sd_above_lim' & `beta2_above_lim' & [`ser1_above_lim',`ser2_above_lim'] & `N_above_lim' & `Neff_above_lim' & `bw_above_lim' & `pval2_above_lim' \\
{res}{txt}
{com}. 
.         
.         tex \addlinespace
{res}{txt}
{com}.         tex \midrule[1 pt]
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \scriptsize{c -(}
{res}{txt}
{com}.         tex Columns 1 and 2 report the descriptive statistics. Column 3 reports local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth (reported in column 7). Columns 4 and 8 report 95\% robust confidence intervals and robust p-values computed following \citep{c -(}calonico_robust_2014{c )-}. Columns 5 and 6 report total observations and observations in optimal MSE bandwidth. Sanctioned indicates the candidate has been sanctioned by the Office of the Inspector General. Donors and Donations include the totals for non-family and family donors. Family is the fraction of donors who are family members of the candidate. Above limit is the fraction of donors contributing above the individual legal limit. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}center{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableC2.do"
{txt}
{com}. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. 
.         global balance_muni lown_resources potencial armed_actor rural_pop_t q_education y_mw
{txt}
{com}.         global balance_ind women age black indi_bkg leftist rightwing sanc_before ilegal pol_exp_d elec_exp_d 
{txt}
{com}.         global balance_fin all total_income donations_total 
{txt}
{com}.         global balance_donors family cont_donor_102 cont_donor_101 contraloria above_lim   
{txt}
{com}.         global balance_all $balance_ind $balance_fin $balance_donors
{txt}
{com}. 
. 
. 
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableC2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableC2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableC2.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Close-election municipality characteristics{c )-}\label{c -(}tab:repr{c )-}
{res}{txt}
{com}.         tex \begin{c -(}center{c )-}
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}%
{res}{txt}
{com}.         tex {c -(}\normalsize
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c {c )-}
{res}{txt}
{com}.         tex \toprule[1.5pt]
{res}{txt}
{com}.         tex \multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}{c )-} & Mean&  Mean & p-value  \\
{res}{txt}
{com}.         tex \multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}{c )-} & Margin. $>$ 0.1 &  Margin. $\leq $ 0.1 & $H_0$: \text{c -(}No difference in means{c )-} \\
{res}{txt}
{com}.         tex \hline
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         
.         
.         use "Data\muni_charac_rep.dta",clear
{txt}
{com}. 
.         replace potencial=potencial/1000
{txt}(1,122 real changes made)

{com}.         replace y_mw=y_mw/100
{txt}(1,067 real changes made)

{com}.         
.         foreach x in $balance_muni{c -(}
{txt}  2{com}. 
.                 ttest `x', by(close_el)
{txt}  3{com}.                 
.                 local mu_1_`x' : di %5.3f `r(mu_1)'
{txt}  4{com}.                 local mu_2_`x' : di %5.3f `r(mu_2)'
{txt}  5{com}.                 local p_val_`x' : di %5.3f `r(p)'
{txt}  6{com}.         {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    221{col 22}  63.5688{col 34}  1.70637{col 46} 25.36702{col 58} 60.20588{col 70} 66.93173
       {txt}1 {c |}{res}{col 12}    572{col 22} 55.50863{col 34} 1.058739{col 46} 25.32136{col 58} 53.42913{col 70} 57.58813
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    793{col 22} 57.75491{col 34} .9081949{col 46}   25.575{col 58} 55.97215{col 70} 59.53766
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 8.060174{col 34} 2.006538{col 58} 4.121405{col 70} 11.99894
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  4.0170
{txt}H0: diff = 0                                     Degrees of freedom = {res}     791

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0001          {txt}Pr(T > t) = {res}0.0000

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    221{col 22} 44.15595{col 34} 9.118056{col 46} 135.5497{col 58} 26.18604{col 70} 62.12587
       {txt}1 {c |}{res}{col 12}    572{col 22} 29.98112{col 34} 8.979403{col 46} 214.7561{col 58} 12.34443{col 70} 47.61781
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    793{col 22} 33.93148{col 34} 6.958264{col 46} 195.9465{col 58} 20.27266{col 70}  47.5903
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 14.17484{col 34} 15.52121{col 58}-16.29279{col 70} 44.64246
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.9133
{txt}H0: diff = 0                                     Degrees of freedom = {res}     791

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8193         {txt}Pr(|T| > |t|) = {res}0.3614          {txt}Pr(T > t) = {res}0.1807

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    221{col 22} .2760181{col 34} .0301385{col 46} .4480407{col 58}  .216621{col 70} .3354152
       {txt}1 {c |}{res}{col 12}    572{col 22} .2167832{col 34} .0172439{col 46} .4124144{col 58}  .182914{col 70} .2506525
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    793{col 22} .2332913{col 34}  .015028{col 46}  .423193{col 58} .2037918{col 70} .2627908
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0592349{col 34} .0334732{col 58}-.0064719{col 70} .1249417
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.7696
{txt}H0: diff = 0                                     Degrees of freedom = {res}     791

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9614         {txt}Pr(|T| > |t|) = {res}0.0772          {txt}Pr(T > t) = {res}0.0386

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    221{col 22} .5086652{col 34} .0170253{col 46} .2530996{col 58} .4751116{col 70} .5422188
       {txt}1 {c |}{res}{col 12}    572{col 22} .5473088{col 34} .0100805{col 46} .2410916{col 58} .5275093{col 70} .5671083
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    793{col 22} .5365393{col 34} .0086984{col 46} .2449505{col 58} .5194645{col 70}  .553614
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0386436{col 34} .0193644{col 58}-.0766554{col 70}-.0006319
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.9956
{txt}H0: diff = 0                                     Degrees of freedom = {res}     791

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0232         {txt}Pr(|T| > |t|) = {res}0.0463          {txt}Pr(T > t) = {res}0.9768

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    216{col 22} .3515456{col 34} .0221207{col 46} .3251061{col 58} .3079445{col 70} .3951468
       {txt}1 {c |}{res}{col 12}    552{col 22} .3948779{col 34} .0153772{col 46} .3612824{col 58} .3646728{col 70}  .425083
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    768{col 22} .3826907{col 34} .0126951{col 46} .3518159{col 58} .3577695{col 70} .4076119
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0433322{col 34} .0282108{col 58}-.0987119{col 70} .0120474
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.5360
{txt}H0: diff = 0                                     Degrees of freedom = {res}     766

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0625         {txt}Pr(|T| > |t|) = {res}0.1249          {txt}Pr(T > t) = {res}0.9375

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    218{col 22} 354.7324{col 34} 97.95974{col 46} 1446.358{col 58}  161.658{col 70} 547.8068
       {txt}1 {c |}{res}{col 12}    556{col 22} 385.6068{col 34} 226.5032{col 46} 5340.866{col 58}-59.30147{col 70} 830.5151
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    774{col 22} 376.9109{col 34} 164.9829{col 46} 4589.965{col 58}  53.0433{col 70} 700.7786
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-30.87444{col 34} 367.0231{col 58} -751.356{col 70} 689.6071
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -0.0841
{txt}H0: diff = 0                                     Degrees of freedom = {res}     772

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.4665         {txt}Pr(|T| > |t|) = {res}0.9330          {txt}Pr(T > t) = {res}0.5335
{txt}
{com}.         
.         
.         
.         use  "Data\cand_level_persist_rep.dta",clear
{txt}
{com}.         
.         drop if margin_victory==.
{txt}(439 observations deleted)

{com}.         gen close_el=0
{txt}
{com}.         replace close_el=1 if abs(margin_victory)<=.1
{txt}(756 real changes made)

{com}.         
.         foreach x in $balance_all{c -(}
{txt}  2{com}.         
.                 ttest `x', by(close_el)
{txt}  3{com}.                 
.                 local mu_1_`x' : di %5.3f `r(mu_1)'
{txt}  4{com}.                 local mu_2_`x' : di %5.3f `r(mu_2)'
{txt}  5{com}.                 local p_val_`x' : di %5.3f `r(p)'
{txt}  6{com}.         {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .1218274{col 34} .0164993{col 46} .3275022{col 58} .0893894{col 70} .1542654
       {txt}1 {c |}{res}{col 12}    756{col 22} .1137566{col 34} .0115556{col 46} .3177256{col 58} .0910717{col 70} .1364415
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .1165217{col 34} .0094655{col 46} .3209891{col 58} .0979502{col 70} .1350932
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0080708{col 34} .0199521{col 58}-.0310758{col 70} .0472174
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.4045
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.6570         {txt}Pr(|T| > |t|) = {res}0.6859          {txt}Pr(T > t) = {res}0.3430

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    359{col 22} 45.31755{col 34} .4936045{col 46} 9.352471{col 58} 44.34682{col 70} 46.28828
       {txt}1 {c |}{res}{col 12}    688{col 22} 44.69477{col 34}  .377134{col 46} 9.892133{col 58} 43.95429{col 70} 45.43524
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,047{col 22} 44.90831{col 34} .3001014{col 46} 9.710494{col 58} 44.31944{col 70} 45.49718
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .6227813{col 34} .6322362{col 58}-.6178158{col 70} 1.863378
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.9850
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1045

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8376         {txt}Pr(|T| > |t|) = {res}0.3248          {txt}Pr(T > t) = {res}0.1624

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    359{col 22} .0362117{col 34} .0098736{col 46} .1870773{col 58} .0167942{col 70} .0556292
       {txt}1 {c |}{res}{col 12}    688{col 22}  .059593{col 34} .0090319{col 46} .2369035{col 58} .0418597{col 70} .0773264
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,047{col 22} .0515759{col 34} .0068385{col 46}  .221275{col 58} .0381572{col 70} .0649946
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0233813{col 34} .0143954{col 58}-.0516286{col 70} .0048659
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.6242
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1045

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0523         {txt}Pr(|T| > |t|) = {res}0.1046          {txt}Pr(T > t) = {res}0.9477

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    359{col 22}  .097493{col 34} .0156773{col 46}  .297042{col 58} .0666619{col 70} .1283242
       {txt}1 {c |}{res}{col 12}    688{col 22} .1380814{col 34}  .013162{col 46} .3452364{col 58} .1122388{col 70}  .163924
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,047{col 22} .1241643{col 34} .0101963{col 46} .3299265{col 58} .1041567{col 70} .1441719
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0405884{col 34} .0214543{col 58}-.0826868{col 70} .0015101
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.8919
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1045

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0294         {txt}Pr(|T| > |t|) = {res}0.0588          {txt}Pr(T > t) = {res}0.9706

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .0203046{col 34} .0071145{col 46} .1412194{col 58} .0063173{col 70} .0342919
       {txt}1 {c |}{res}{col 12}    756{col 22} .0330688{col 34} .0065078{col 46} .1789346{col 58} .0202933{col 70} .0458443
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .0286957{col 34} .0049252{col 46} .1670224{col 58} .0190322{col 70} .0383591
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0127642{col 34} .0103757{col 58}-.0331217{col 70} .0075933
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.2302
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.1094         {txt}Pr(|T| > |t|) = {res}0.2189          {txt}Pr(T > t) = {res}0.8906

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22}  .251269{col 34} .0218794{col 46} .4342944{col 58} .2082537{col 70} .2942844
       {txt}1 {c |}{res}{col 12}    756{col 22} .2433862{col 34} .0156175{col 46} .4294104{col 58} .2127273{col 70} .2740451
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22}  .246087{col 34} .0127071{col 46} .4309172{col 58} .2211553{col 70} .2710186
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0078828{col 34} .0267859{col 58} -.044672{col 70} .0604376
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.2943
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.6157         {txt}Pr(|T| > |t|) = {res}0.7686          {txt}Pr(T > t) = {res}0.3843

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .1116751{col 34} .0158879{col 46} .3153668{col 58} .0804391{col 70} .1429111
       {txt}1 {c |}{res}{col 12}    756{col 22} .1044974{col 34}  .011133{col 46} .3061072{col 58}  .082642{col 70} .1263527
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .1069565{col 34} .0091176{col 46} .3091924{col 58} .0890675{col 70} .1248455
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0071778{col 34}  .019219{col 58}-.0305306{col 70} .0448861
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.3735
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.6456         {txt}Pr(|T| > |t|) = {res}0.7089          {txt}Pr(T > t) = {res}0.3544

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .0025381{col 34} .0025381{col 46} .0503793{col 58}-.0024518{col 70}  .007528
       {txt}1 {c |}{res}{col 12}    756{col 22} .0039683{col 34}  .002288{col 46} .0629106{col 58}-.0005234{col 70} .0084599
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .0034783{col 34} .0017369{col 46} .0588997{col 58} .0000705{col 70}  .006886
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0014302{col 34} .0036611{col 58}-.0086134{col 70}  .005753
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -0.3906
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.3481         {txt}Pr(|T| > |t|) = {res}0.6961          {txt}Pr(T > t) = {res}0.6519

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .4492386{col 34} .0250913{col 46}  .498049{col 58} .3999085{col 70} .4985686
       {txt}1 {c |}{res}{col 12}    754{col 22} .4363395{col 34} .0180727{col 46}   .49626{col 58} .4008606{col 70} .4718184
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,148{col 22} .4407666{col 34} .0146595{col 46} .4966954{col 58} .4120041{col 70}  .469529
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0128991{col 34} .0308876{col 58}-.0477035{col 70} .0735016
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.4176
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1146

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.6618         {txt}Pr(|T| > |t|) = {res}0.6763          {txt}Pr(T > t) = {res}0.3382

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .3781726{col 34} .0244615{col 46} .4855476{col 58} .3300808{col 70} .4262644
       {txt}1 {c |}{res}{col 12}    754{col 22} .3474801{col 34} .0173526{col 46} .4764859{col 58} .3134149{col 70} .3815453
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,148{col 22} .3580139{col 34} .0141557{col 46} .4796252{col 58}   .33024{col 70} .3857879
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0306925{col 34} .0298145{col 58}-.0278047{col 70} .0891897
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.0294
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1146

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8483         {txt}Pr(|T| > |t|) = {res}0.3035          {txt}Pr(T > t) = {res}0.1517

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22}  6.51269{col 34} .4599429{col 46} 9.129606{col 58} 5.608434{col 70} 7.416947
       {txt}1 {c |}{res}{col 12}    756{col 22} 5.361111{col 34} .3009103{col 46} 8.273665{col 58} 4.770391{col 70} 5.951831
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} 5.755652{col 34}  .253305{col 46}  8.58999{col 58}  5.25866{col 70} 6.252644
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 1.151579{col 34} .5328931{col 58} .1060255{col 70} 2.197133
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  2.1610
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9845         {txt}Pr(|T| > |t|) = {res}0.0309          {txt}Pr(T > t) = {res}0.0155

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} 78.24219{col 34} 7.515578{col 46}   149.18{col 58} 63.46643{col 70} 93.01796
       {txt}1 {c |}{res}{col 12}    756{col 22}  56.7638{col 34} 4.225575{col 46} 116.1841{col 58} 48.46853{col 70} 65.05907
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} 64.12248{col 34} 3.797692{col 46}  128.786{col 58}  56.6713{col 70} 71.57367
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 21.47839{col 34} 7.980531{col 58} 5.820326{col 70} 37.13645
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  2.6913
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9964         {txt}Pr(|T| > |t|) = {res}0.0072          {txt}Pr(T > t) = {res}0.0036

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .5926939{col 34} .0138912{col 46} .2757327{col 58} .5653835{col 70} .6200043
       {txt}1 {c |}{res}{col 12}    756{col 22} .5778838{col 34} .0099534{col 46} .2736736{col 58} .5583441{col 70} .5974235
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .5829579{col 34} .0080902{col 46}  .274351{col 58} .5670847{col 70}  .598831
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0148101{col 34} .0170488{col 58}-.0186401{col 70} .0482603
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.8687
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8074         {txt}Pr(|T| > |t|) = {res}0.3852          {txt}Pr(T > t) = {res}0.1926

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .3920428{col 34} .0203394{col 46}  .403726{col 58} .3520551{col 70} .4320305
       {txt}1 {c |}{res}{col 12}    756{col 22} .4595971{col 34} .0150842{col 46}  .414746{col 58} .4299852{col 70}  .489209
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .4364524{col 34} .0121515{col 46}  .412078{col 58} .4126108{col 70} .4602941
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0675544{col 34} .0255381{col 58} -.117661{col 70}-.0174477
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -2.6452
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0041         {txt}Pr(|T| > |t|) = {res}0.0083          {txt}Pr(T > t) = {res}0.9959

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    297{col 22}   6.0118{col 34} .5296311{col 46} 9.127498{col 58}  4.96948{col 70} 7.054119
       {txt}1 {c |}{res}{col 12}    526{col 22} 5.769183{col 34} .3226564{col 46} 7.400024{col 58} 5.135327{col 70}  6.40304
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    823{col 22} 5.856738{col 34} .2810076{col 46} 8.061539{col 58} 5.305161{col 70} 6.408314
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .2426164{col 34} .5854175{col 58}-.9064748{col 70} 1.391708
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.4144
{txt}H0: diff = 0                                     Degrees of freedom = {res}     821

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.6607         {txt}Pr(|T| > |t|) = {res}0.6787          {txt}Pr(T > t) = {res}0.3393

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    260{col 22} 11.36556{col 34} .9196691{col 46} 14.82922{col 58} 9.554578{col 70} 13.17654
       {txt}1 {c |}{res}{col 12}    518{col 22} 9.658016{col 34} .4788764{col 46} 10.89904{col 58} 8.717233{col 70}  10.5988
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    778{col 22} 10.22866{col 34}  .443449{col 46} 12.36897{col 58}  9.35816{col 70} 11.09916
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 1.707543{col 34} .9387012{col 58}-.1351518{col 70} 3.550238
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.8190
{txt}H0: diff = 0                                     Degrees of freedom = {res}     776

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9654         {txt}Pr(|T| > |t|) = {res}0.0693          {txt}Pr(T > t) = {res}0.0346

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .0069508{col 34} .0022684{col 46} .0450267{col 58} .0024911{col 70} .0114106
       {txt}1 {c |}{res}{col 12}    756{col 22} .0053908{col 34} .0014448{col 46} .0397244{col 58} .0025546{col 70} .0082271
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22} .0059253{col 34} .0012268{col 46} .0416042{col 58} .0035182{col 70} .0083324
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}   .00156{col 34} .0025858{col 58}-.0035135{col 70} .0066334
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.6033
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.7268         {txt}Pr(|T| > |t|) = {res}0.5464          {txt}Pr(T > t) = {res}0.2732

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    394{col 22} .2405454{col 34} .0186634{col 46} .3704583{col 58} .2038528{col 70} .2772381
       {txt}1 {c |}{res}{col 12}    756{col 22} .2816953{col 34} .0140907{col 46} .3874305{col 58} .2540336{col 70} .3093569
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,150{col 22}  .267597{col 34} .0112657{col 46} .3820391{col 58} .2454933{col 70} .2897007
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0411498{col 34} .0237175{col 58}-.0876842{col 70} .0053846
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.7350
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1148

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0415         {txt}Pr(|T| > |t|) = {res}0.0830          {txt}Pr(T > t) = {res}0.9585
{txt}
{com}.         
.         
.         
.                 
.         *Table continue
.         tex \multicolumn{c -(}4{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel A: Municipality characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         tex \ Local revenue (\% of total) & `mu_1_lown_resources' & `mu_2_lown_resources' & `p_val_lown_resources' \\
{res}{txt}
{com}.         tex \ Registered voters & `mu_1_potencial' & `mu_2_potencial' & `p_val_potencial' \\
{res}{txt}
{com}.         tex \ Armed group & `mu_1_armed_actor' & `mu_2_armed_actor' & `p_val_armed_actor' \\
{res}{txt}
{com}.         tex \ Rural population & `mu_1_rural_pop_t' & `mu_2_rural_pop_t' & `p_val_rural_pop_t'  \\
{res}{txt}
{com}.         tex \ Underperforming schools & `mu_1_q_education' & `mu_2_q_education' & `p_val_q_education' \\
{res}{txt}
{com}.         tex \ Discretionary revenue & `mu_1_y_mw' & `mu_2_y_mw' & `p_val_y_mw' \\
{res}{txt}
{com}. tex \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}4{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel B: Candidates characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         tex \ Women & `mu_1_women' & `mu_2_women' & `p_val_women' \\
{res}{txt}
{com}.         tex \ Age & `mu_1_age' & `mu_2_age' & `p_val_age' \\
{res}{txt}
{com}.         tex \ Black & `mu_1_black' & `mu_2_black' & `p_val_black' \\
{res}{txt}
{com}.         tex \ Indigenous & `mu_1_indi_bkg' & `mu_2_indi_bkg' & `p_val_indi_bkg'  \\
{res}{txt}
{com}.         tex \ Left wing & `mu_1_leftist' & `mu_2_leftist' & `p_val_leftist' \\
{res}{txt}
{com}.         tex \ Right wing & `mu_1_rightwing' & `mu_2_rightwing' & `p_val_rightwing' \\
{res}{txt}
{com}.         tex \ Sanctioned & `mu_1_sanc_before' & `mu_2_sanc_before' & `p_val_sanc_before' \\
{res}{txt}
{com}.         tex \ Illegal Registration of ID. & `mu_1_ilegal' & `mu_2_ilegal' & `p_val_ilegal' \\
{res}{txt}
{com}.         tex \ Political experience & `mu_1_pol_exp_d' & `mu_2_pol_exp_d' & `p_val_pol_exp_d' \\
{res}{txt}
{com}.         tex \ Held office before & `mu_1_elec_exp_d' & `mu_2_elec_exp_d' & `p_val_elec_exp_d' \\
{res}{txt}
{com}.         tex \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}4{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel C: General funding covariates{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Donors & `mu_1_all' & `mu_2_all' & `p_val_all' \\
{res}{txt}
{com}.         tex \ Campaign revenue & `mu_1_total_income' & `mu_2_total_income' & `p_val_total_income'  \\
{res}{txt}
{com}.         tex \ Donations /Revenue & `mu_1_donations_total' & `mu_2_donations_total' & `p_val_donations_total' \\
{res}{txt}
{com}. 
.         tex \\
{res}{txt}
{com}.         tex \multicolumn{c -(}4{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel D: Donors characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Family & `mu_1_family' & `mu_2_family' & `p_val_family'\\
{res}{txt}
{com}.         tex \ Avg. Donation (private) & `mu_1_cont_donor_102' & `mu_2_cont_donor_102' & `p_val_cont_donor_102' \\
{res}{txt}
{com}.         tex \ Avg. Donation (family) & `mu_1_cont_donor_101' & `mu_2_cont_donor_101' & `p_val_cont_donor_101' \\
{res}{txt}
{com}.         tex \ Comptroller sanction & `mu_1_contraloria' & `mu_2_contraloria' & `p_val_contraloria' \\
{res}{txt}
{com}.         tex \ Above limit & `mu_1_above_lim' & `mu_2_above_lim' & `p_val_above_lim' \\
{res}{txt}
{com}. 
. 
.         
.         tex \addlinespace
{res}{txt}
{com}.         tex \midrule[1 pt]
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \scriptsize{c -(}
{res}{txt}
{com}.         tex Local revenue denotes the percentage of own resources in all resources of the municipality. Armed group indicates the presence of guerrillas or paramilitary forces. Underperforming schools is the share of schools in the municipality classified below average performance by the Instituto Colombiano para la Evaluaci\'on de la Educaci\'on. Rural population is the share of the population living in rural areas. Sanctioned indicates the candidate has been sanctioned by the Office of the Inspector General. Donors and Donations include totals for non-family and family donors. Family is the fraction of donors who are family members of the candidate. Above limit is the fraction of donors contributing above the individual legal limit.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}center{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableF1.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. gen margin_victory_sq=margin_victory^2
{txt}(439 missing values generated)

{com}. gen treat_margin_victory_sq=treat*margin_victory_sq     
{txt}(439 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableF1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableF1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableF1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (global quadratic parametric RD){c )-}\label{c -(}tab:donations_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5 {c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress `x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`x' : di %5.3f r(sd)           
{txt}  6{com}.                 
.                 regress `x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  7{com}. 
.                 local N_`x' : di %5.0f e(N)
{txt}  8{com}.                 local R2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,150
                                                {txt}F(5, 792)         =  {res}     6.71
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0317
                                                {txt}Root MSE          =    {res} .21811

{txt}{ralign 89:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}           donate_15any{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.1001977{col 37}{space 2} .0292284{col 48}{space 1}   -3.43{col 57}{space 3}0.001{col 65}{space 4}-.1575719{col 78}{space 3}-.0428235
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2}-.7162616{col 37}{space 2} 2.106702{col 48}{space 1}   -0.34{col 57}{space 3}0.734{col 65}{space 4}-4.851641{col 78}{space 3} 3.419118
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2} .8208251{col 37}{space 2}  1.86003{col 48}{space 1}    0.44{col 57}{space 3}0.659{col 65}{space 4}-2.830347{col 78}{space 3} 4.471997
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2}-.2834604{col 37}{space 2} .5349588{col 48}{space 1}   -0.53{col 57}{space 3}0.596{col 65}{space 4}-1.333565{col 78}{space 3} .7666444
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .3271904{col 37}{space 2} .4945897{col 48}{space 1}    0.66{col 57}{space 3}0.508{col 65}{space 4}-.6436712{col 78}{space 3} 1.298052
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .1584627{col 37}{space 2} .0261309{col 48}{space 1}    6.06{col 57}{space 3}0.000{col 65}{space 4} .1071687{col 78}{space 3} .2097566
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}     1,150
                                                {txt}F(5, 792)         =  {res}     6.40
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0255
                                                {txt}Root MSE          =    {res} .18775

{txt}{ralign 89:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                     b5{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.0827528{col 37}{space 2} .0247883{col 48}{space 1}   -3.34{col 57}{space 3}0.001{col 65}{space 4}-.1314113{col 78}{space 3}-.0340943
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2} -.571711{col 37}{space 2} 1.588899{col 48}{space 1}   -0.36{col 57}{space 3}0.719{col 65}{space 4}-3.690662{col 78}{space 3}  2.54724
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2}-.1067932{col 37}{space 2} 1.505566{col 48}{space 1}   -0.07{col 57}{space 3}0.943{col 65}{space 4}-3.062164{col 78}{space 3} 2.848578
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2} .0279116{col 37}{space 2} .4386892{col 48}{space 1}    0.06{col 57}{space 3}0.949{col 65}{space 4}-.8332195{col 78}{space 3} .8890427
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .1787534{col 37}{space 2} .4185259{col 48}{space 1}    0.43{col 57}{space 3}0.669{col 65}{space 4}-.6427978{col 78}{space 3} 1.000305
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .1127502{col 37}{space 2} .0228238{col 48}{space 1}    4.94{col 57}{space 3}0.000{col 65}{space 4}  .067948{col 78}{space 3} .1575525
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         
.         *Continue table
.         tex Electoral victory & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\  \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}OLS estimates of average treatment effects at the cutoff.  Controls include the interaction of the treatment with running variable and running variable, interaction of the treatment with the squared running variable, and the running variable squared. P-values and 95\% robust confidence intervals with clustering at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableF2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}. gen margin_victory_sq=margin_victory^2
{txt}(439 missing values generated)

{com}. gen treat_margin_victory_sq=treat*margin_victory_sq
{txt}(439 missing values generated)

{com}.         ******************
.         *       TABL
.         *****************
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableF2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableF2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableF2.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on benefits to donors (global parametric linear RD){c )-}\label{c -(}tab:table_benefits_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.                 tex \scalebox{c -(}.8{c )-}{c -(}
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l H H c c c c{c )-} \hline
{res}{txt}
{com}. tex Outcome:& &&\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Receive contract{c )-}&Receive contract& Runs in 2015\\
{res}{txt}
{com}.         tex & & &\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} & (outside)& \\
{res}{txt}
{com}.         tex & Non-Family &Family & Non-Family &Family  & Family &Family \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4)& (5) & (6)\\ \hline
{res}{txt}
{com}.         tex & & & & & &\\
{res}{txt}
{com}.         
.         *preserve
.         *drop contract
.         *rename got_any contract
.         
.         *Model 1
.         foreach x in   contract{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress nf`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum nf`x' if e(sample)
{txt}  4{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 regress nf`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt}  7{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
. 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}       823
                                                {txt}F(5, 614)         =  {res}     5.71
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0261
                                                {txt}Root MSE          =    {res} .20681

{txt}{ralign 89:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}             nfcontract{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2} .0704012{col 37}{space 2} .0308493{col 48}{space 1}    2.28{col 57}{space 3}0.023{col 65}{space 4} .0098183{col 78}{space 3} .1309842
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2} 1.620316{col 37}{space 2} 1.796626{col 48}{space 1}    0.90{col 57}{space 3}0.367{col 65}{space 4}-1.907962{col 78}{space 3} 5.148593
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2}-.9643745{col 37}{space 2} .9926997{col 48}{space 1}   -0.97{col 57}{space 3}0.332{col 65}{space 4}-2.913873{col 78}{space 3}  .985124
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2} .1649126{col 37}{space 2} .5572382{col 48}{space 1}    0.30{col 57}{space 3}0.767{col 65}{space 4}-.9294114{col 78}{space 3} 1.259237
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2}-.2179738{col 37}{space 2} .3270111{col 48}{space 1}   -0.67{col 57}{space 3}0.505{col 65}{space 4}-.8601697{col 78}{space 3}  .424222
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .0525744{col 37}{space 2}  .019281{col 48}{space 1}    2.73{col 57}{space 3}0.007{col 65}{space 4} .0147097{col 78}{space 3} .0904392
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         
.         foreach x in  contract got_above_ext runs_any{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly sum f`x' 
{txt}  3{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  5{com}.                 
.                 regress f`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt}  6{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  7{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  8{com}. 
.                 matrix b = e(b)
{txt}  9{com}.                 matrix v = e(V)
{txt} 10{com}.                 matrix res=r(table)
{txt} 11{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 12{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 13{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 14{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 15{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 16{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}       778
                                                {txt}F(5, 612)         =  {res}     0.94
                                                {txt}Prob > F          = {res}    0.4559
                                                {txt}R-squared         = {res}    0.0042
                                                {txt}Root MSE          =    {res} .04901

{txt}{ralign 89:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}              fcontract{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2} -.002161{col 37}{space 2} .0025727{col 48}{space 1}   -0.84{col 57}{space 3}0.401{col 65}{space 4}-.0072133{col 78}{space 3} .0028913
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2}-.5313309{col 37}{space 2} .8585471{col 48}{space 1}   -0.62{col 57}{space 3}0.536{col 65}{space 4}-2.217387{col 78}{space 3} 1.154725
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2} .3311518{col 37}{space 2} .8313762{col 48}{space 1}    0.40{col 57}{space 3}0.691{col 65}{space 4}-1.301545{col 78}{space 3} 1.963848
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2} .0397321{col 37}{space 2} .1277659{col 48}{space 1}    0.31{col 57}{space 3}0.756{col 65}{space 4}-.2111807{col 78}{space 3} .2906449
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .0092409{col 37}{space 2} .1161584{col 48}{space 1}    0.08{col 57}{space 3}0.937{col 65}{space 4}-.2188766{col 78}{space 3} .2373584
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .0030119{col 37}{space 2} .0024535{col 48}{space 1}    1.23{col 57}{space 3}0.220{col 65}{space 4}-.0018063{col 78}{space 3} .0078302
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}       778
                                                {txt}F(5, 612)         =  {res}     1.45
                                                {txt}Prob > F          = {res}    0.2059
                                                {txt}R-squared         = {res}    0.0101
                                                {txt}Root MSE          =    {res} .23658

{txt}{ralign 89:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}         fgot_above_ext{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}  .013554{col 37}{space 2} .0338519{col 48}{space 1}    0.40{col 57}{space 3}0.689{col 65}{space 4} -.052926{col 78}{space 3}  .080034
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2} 2.674201{col 37}{space 2} 2.577179{col 48}{space 1}    1.04{col 57}{space 3}0.300{col 65}{space 4}-2.386986{col 78}{space 3} 7.735389
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2}-2.925728{col 37}{space 2} 2.180699{col 48}{space 1}   -1.34{col 57}{space 3}0.180{col 65}{space 4} -7.20829{col 78}{space 3} 1.356834
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2} .9481297{col 37}{space 2} .7242694{col 48}{space 1}    1.31{col 57}{space 3}0.191{col 65}{space 4}-.4742251{col 78}{space 3} 2.370485
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2}-.9497741{col 37}{space 2}  .581789{col 48}{space 1}   -1.63{col 57}{space 3}0.103{col 65}{space 4}-2.092319{col 78}{space 3} .1927708
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .0713369{col 37}{space 2} .0266888{col 48}{space 1}    2.67{col 57}{space 3}0.008{col 65}{space 4} .0189242{col 78}{space 3} .1237496
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}       778
                                                {txt}F(5, 612)         =  {res}     0.87
                                                {txt}Prob > F          = {res}    0.5020
                                                {txt}R-squared         = {res}    0.0052
                                                {txt}Root MSE          =    {res} .09757

{txt}{ralign 89:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}              fruns_any{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.0236051{col 37}{space 2} .0177462{col 48}{space 1}   -1.33{col 57}{space 3}0.184{col 65}{space 4}-.0584559{col 78}{space 3} .0112458
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2}-1.637038{col 37}{space 2} .9535283{col 48}{space 1}   -1.72{col 57}{space 3}0.087{col 65}{space 4}-3.509623{col 78}{space 3} .2355461
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2} 1.296513{col 37}{space 2} .8538324{col 48}{space 1}    1.52{col 57}{space 3}0.129{col 65}{space 4}-.3802835{col 78}{space 3}  2.97331
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2}-.1559476{col 37}{space 2} .2911793{col 48}{space 1}   -0.54{col 57}{space 3}0.592{col 65}{space 4}-.7277794{col 78}{space 3} .4158843
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .3356774{col 37}{space 2} .2483559{col 48}{space 1}    1.35{col 57}{space 3}0.177{col 65}{space 4}-.1520558{col 78}{space 3} .8234106
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .0267371{col 37}{space 2} .0163114{col 48}{space 1}    1.64{col 57}{space 3}0.102{col 65}{space 4}-.0052961{col 78}{space 3} .0587703
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         
. 
.         *Continue table
.         tex Electoral victory & `nfb1_total_cont_num_d' &  `fb1_total_cont_num_d'& `nfb1_contract' & `fb1_contract' & `fb1_got_above_ext' & `fb1_runs_any' \\
{res}{txt}
{com}. 
.         tex \ \ \ \  p-value & `nfp_v_total_cont_num_d' &  `fp_v_total_cont_num_d' & `nfp_v_contract' & `fp_v_contract' & `fp_v_got_above_ext' & `fp_v_runs_any' \\
{res}{txt}
{com}.         
.         
.         tex \ \ \ \ CI 95\%  & [`nflci_total_cont_num_d',`nflci_total_cont_num_d'] & [`flci_total_cont_num_d',`fuci_total_cont_num_d'] &  [`nflci_contract',`nfuci_contract'] & [`flci_contract',`fuci_contract'] & [`flci_got_above_ext',`fuci_got_above_ext'] & [`flci_runs_any',`fuci_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations &`nfN_total_cont_num_d' &  `fN_total_cont_num_d' & `nfN_contract'& `fN_contract' & `fN_got_above_ext' & `fN_runs_any' \\
{res}{txt}
{com}.         tex Mean & `nfmean_total_cont_num_d' &`fmean_total_cont_num_d'  &  `nfmean_contract' & `fmean_contract' & `fmean_got_above_ext' & `fmean_runs_any' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} 
{res}{txt}
{com}.         tex \footnotesize{c -(}OLS estimates of average treatment effects at the cutoff. Controls include the interaction of the treatment with running variable and running variable, interaction of the treatment with the squared running variable, and the running variable squared. P-values and 95\% robust confidence intervals with clustering at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableF3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear     
{txt}
{com}.                 
.         gen treat=0
{txt}
{com}.         replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(632 real changes made)

{com}.         replace treat=. if margin_victory==.
{txt}(439 real changes made, 439 to missing)

{com}. 
.         gen treat_margin_victory=treat*margin_victory
{txt}(439 missing values generated)

{com}.         gen margin_victory_sq=margin_victory^2
{txt}(439 missing values generated)

{com}.         gen treat_margin_victory_sq=treat*margin_victory_sq
{txt}(439 missing values generated)

{com}. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableF3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableF3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableF3.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members global parametric quadratic RD){c )-}\label{c -(}tab:donation_fam_nofam_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c {c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor  \\ 
{res}{txt}
{com}.         tex & (1) & (2)  \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}\\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.                 
. 
.                 
.                 quietly: regress f`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt}  3{com}. 
.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 regress f`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 17{com}. 
.                                 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                         quietly: regress nf`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt} 18{com}.                         quietly sum nf`x' if e(sample)
{txt} 19{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt} 20{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt} 21{com}.                 
.                 regress nf`x' treat treat_margin_victory_sq margin_victory_sq treat_margin_victory margin_victory, vce(cluster muni_code)
{txt} 22{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt} 23{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt} 24{com}. 
.                 matrix b = e(b)
{txt} 25{com}.                 matrix v = e(V)
{txt} 26{com}.                 matrix res=r(table)
{txt} 27{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 28{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 29{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 30{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 31{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 32{com}.         {c )-}

{txt}Linear regression                               Number of obs     = {res}       778
                                                {txt}F(5, 612)         =  {res}    11.76
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0827
                                                {txt}Root MSE          =    {res} .24063

{txt}{ralign 89:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}          fdonate_15any{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2} -.172115{col 37}{space 2} .0433799{col 48}{space 1}   -3.97{col 57}{space 3}0.000{col 65}{space 4}-.2573066{col 78}{space 3}-.0869234
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2}-1.504454{col 37}{space 2} 3.239625{col 48}{space 1}   -0.46{col 57}{space 3}0.643{col 65}{space 4}-7.866585{col 78}{space 3} 4.857676
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2} 2.458087{col 37}{space 2} 3.127504{col 48}{space 1}    0.79{col 57}{space 3}0.432{col 65}{space 4}-3.683856{col 78}{space 3} 8.600029
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2}-.8699371{col 37}{space 2}   .86046{col 48}{space 1}   -1.01{col 57}{space 3}0.312{col 65}{space 4} -2.55975{col 78}{space 3} .8198752
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .7108624{col 37}{space 2} .8066347{col 48}{space 1}    0.88{col 57}{space 3}0.379{col 65}{space 4}-.8732454{col 78}{space 3}  2.29497
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  .200282{col 37}{space 2} .0418992{col 48}{space 1}    4.78{col 57}{space 3}0.000{col 65}{space 4} .1179984{col 78}{space 3} .2825656
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}       823
                                                {txt}F(5, 614)         =  {res}     1.47
                                                {txt}Prob > F          = {res}    0.1993
                                                {txt}R-squared         = {res}    0.0092
                                                {txt}Root MSE          =    {res} .23084

{txt}{ralign 89:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}         nfdonate_15any{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.0539376{col 37}{space 2} .0342676{col 48}{space 1}   -1.57{col 57}{space 3}0.116{col 65}{space 4}-.1212334{col 78}{space 3} .0133583
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2} .7074192{col 37}{space 2} 2.457875{col 48}{space 1}    0.29{col 57}{space 3}0.774{col 65}{space 4}-4.119443{col 78}{space 3} 5.534281
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2}-1.356426{col 37}{space 2} 2.251351{col 48}{space 1}   -0.60{col 57}{space 3}0.547{col 65}{space 4}-5.777708{col 78}{space 3} 3.064855
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2}  .407932{col 37}{space 2} .6535765{col 48}{space 1}    0.62{col 57}{space 3}0.533{col 65}{space 4}-.8755846{col 78}{space 3} 1.691449
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2}-.1703285{col 37}{space 2} .5804467{col 48}{space 1}   -0.29{col 57}{space 3}0.769{col 65}{space 4} -1.31023{col 78}{space 3} .9695731
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .1292546{col 37}{space 2} .0290988{col 48}{space 1}    4.44{col 57}{space 3}0.000{col 65}{space 4} .0721093{col 78}{space 3} .1863999
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}       778
                                                {txt}F(5, 612)         =  {res}    11.95
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0798
                                                {txt}Root MSE          =    {res} .21839

{txt}{ralign 89:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                    fb5{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.1415034{col 37}{space 2} .0385769{col 48}{space 1}   -3.67{col 57}{space 3}0.000{col 65}{space 4}-.2172625{col 78}{space 3}-.0657443
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2}-1.211638{col 37}{space 2} 2.921491{col 48}{space 1}   -0.41{col 57}{space 3}0.678{col 65}{space 4}-6.949002{col 78}{space 3} 4.525726
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2} .9023815{col 37}{space 2} 2.938687{col 48}{space 1}    0.31{col 57}{space 3}0.759{col 65}{space 4}-4.868752{col 78}{space 3} 6.673515
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2}-.1846282{col 37}{space 2} .7791056{col 48}{space 1}   -0.24{col 57}{space 3}0.813{col 65}{space 4}-1.714673{col 78}{space 3} 1.345417
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2} .2496871{col 37}{space 2} .7532095{col 48}{space 1}    0.33{col 57}{space 3}0.740{col 65}{space 4}-1.229502{col 78}{space 3} 1.728876
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .1535685{col 37}{space 2} .0380448{col 48}{space 1}    4.04{col 57}{space 3}0.000{col 65}{space 4} .0788543{col 78}{space 3} .2282827
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}       823
                                                {txt}F(5, 614)         =  {res}     1.70
                                                {txt}Prob > F          = {res}    0.1325
                                                {txt}R-squared         = {res}    0.0060
                                                {txt}Root MSE          =    {res} .19113

{txt}{ralign 89:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   nfb5{col 25}{c |} Coefficient{col 37}  std. err.{col 49}      t{col 57}   P>|t|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}treat {c |}{col 25}{res}{space 2}-.0357185{col 37}{space 2} .0274223{col 48}{space 1}   -1.30{col 57}{space 3}0.193{col 65}{space 4}-.0895713{col 78}{space 3} .0181344
{txt}treat_margin_victory_sq {c |}{col 25}{res}{space 2} .7319343{col 37}{space 2} 1.724473{col 48}{space 1}    0.42{col 57}{space 3}0.671{col 65}{space 4}-2.654646{col 78}{space 3} 4.118514
{txt}{space 6}margin_victory_sq {c |}{col 25}{res}{space 2}-1.511927{col 37}{space 2} 1.544701{col 48}{space 1}   -0.98{col 57}{space 3}0.328{col 65}{space 4}-4.545465{col 78}{space 3} 1.521611
{txt}{space 3}treat_margin_victory {c |}{col 25}{res}{space 2} .4285834{col 37}{space 2} .5080793{col 48}{space 1}    0.84{col 57}{space 3}0.399{col 65}{space 4}-.5692005{col 78}{space 3} 1.426367
{txt}{space 9}margin_victory {c |}{col 25}{res}{space 2}-.1690073{col 37}{space 2} .4416754{col 48}{space 1}   -0.38{col 57}{space 3}0.702{col 65}{space 4}-1.036385{col 78}{space 3} .6983704
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  .078914{col 37}{space 2} .0236689{col 48}{space 1}    3.33{col 57}{space 3}0.001{col 65}{space 4} .0324322{col 78}{space 3} .1253958
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Continue table
.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `fp_v_donate_15any' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_15any',`fuci_donate_15any'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' \\
{res}{txt}
{com}.         tex R-squared & `fR2_donate_15any' & `fR2_b5'  \\ 
{res}{txt}
{com}.         
.         tex & & \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}. 
.                 tex Electoral victory & `nfb1_donate_15any' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `nfp_v_donate_15any' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_15any',`nfuci_donate_15any'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_15any' & `nfN_b5' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_15any' & `nfmean_b5' \\
{res}{txt}
{com}.         tex R-squared & `nfR2_donate_15any' & `nfR2_b5'  \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}OLS estimates of average treatment effects at the cutoff. Controls include the interaction of the treatment with running variable and running variable, interaction of the treatment with the squared running variable, and the running variable squared. P-values and 95\% robust confidence intervals with clustering at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableF4.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. keep muni_code margin_victory fdonate_15any fb5
{txt}
{com}. 
. foreach var in donate_15any b5{c -(}
{txt}  2{com}.     rename  f`var' `var'
{txt}  3{com}. {c )-}
{res}{txt}
{com}. 
. gen family=1
{txt}
{com}. 
. save  "Data\cand_level_persist_fam_aux_rep.dta",replace
{txt}{p 0 4 2}
(file {bf}
Data\cand_level_persist_fam_aux_rep.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Data\cand_level_persist_fam_aux_rep.dta{rm}
saved
{p_end}

{com}. 
. use  "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. keep muni_code margin_victory nfdonate_15any nfb5
{txt}
{com}. 
. foreach var in donate_15any b5{c -(}
{txt}  2{com}.     rename  nf`var' `var'
{txt}  3{com}. {c )-}
{res}{txt}
{com}. 
. gen family=0
{txt}
{com}. 
. append using "Data\cand_level_persist_fam_aux_rep.dta"
{txt}
{com}. 
. 
.                 
.         gen treat=0
{txt}
{com}.         replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(1,264 real changes made)

{com}.         replace treat=. if margin_victory==.
{txt}(878 real changes made, 878 to missing)

{com}. 
.         gen treat_margin_victory=treat*margin_victory
{txt}(878 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableF4.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableF4.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableF4.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members and non-members, interaction global parametric linear RD){c )-}\label{c -(}tab:donation_fam_nofam_inter_l{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c {c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor  \\ 
{res}{txt}
{com}.         tex & (1) & (2)  \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}\\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.                         
.                 quietly: regress `x' (i.treat   c.treat_margin_victory c.margin_victory)##i.family, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 regress `x' (i.treat   c.treat_margin_victory c.margin_victory)##i.family, vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`x' : di %5.3f b[1,2]
{txt} 13{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,2])
{txt} 14{com}.                 local fp_v1_`x' :di %5.3f res[4,2]
{txt} 15{com}.                 local fuci1_`x': di %5.3f res[6,2]
{txt} 16{com}.                 local flci1_`x': di %5.3f res[5,2]
{txt} 17{com}.                 
.                 local fb2_`x' : di %5.3f b[1,10]
{txt} 18{com}.                 local fse2_`x' : di %5.3f sqrt(v[1,10])
{txt} 19{com}.                 local fp_v2_`x' :di %5.3f res[4,10]
{txt} 20{com}.                 local fuci2_`x': di %5.3f res[6,10]
{txt} 21{com}.                 local flci2_`x': di %5.3f res[5,10]
{txt} 22{com}. 
.                 lincom 1.treat+ 1.treat#1.family
{txt} 23{com}.                 
.                 local fb3_`x': di %5.3f r(estimate)
{txt} 24{com}.                 local fp_v3_`x' :di %5.3f r(p)
{txt} 25{com}.                 local fuci3_`x': di %5.3f r(ub)
{txt} 26{com}.                 local flci3_`x': di %5.3f r(lb)
{txt} 27{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,601
                                                {txt}F(7, 792)         =  {res}    15.22
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0481
                                                {txt}Root MSE          =    {res} .23549

{txt}{ralign 95:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                 donate_15any{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}1.treat {c |}{col 31}{res}{space 2}-.0591406{col 43}{space 2} .0259654{col 54}{space 1}   -2.28{col 63}{space 3}0.023{col 71}{space 4}-.1101098{col 84}{space 3}-.0081715
{txt}{space 9}treat_margin_victory {c |}{col 31}{res}{space 2}-.0634349{col 43}{space 2} .2152237{col 54}{space 1}   -0.29{col 63}{space 3}0.768{col 71}{space 4}-.4859113{col 84}{space 3} .3590414
{txt}{space 15}margin_victory {c |}{col 31}{res}{space 2} .1437804{col 43}{space 2} .1686499{col 54}{space 1}    0.85{col 63}{space 3}0.394{col 71}{space 4}-.1872733{col 84}{space 3}  .474834
{txt}{space 21}1.family {c |}{col 31}{res}{space 2}  .042567{col 43}{space 2} .0358584{col 54}{space 1}    1.19{col 63}{space 3}0.236{col 71}{space 4}-.0278217{col 84}{space 3} .1129556
{txt}{space 29} {c |}
{space 17}treat#family {c |}
{space 25}1 1  {c |}{col 31}{res}{space 2}-.1051146{col 43}{space 2} .0406751{col 54}{space 1}   -2.58{col 63}{space 3}0.010{col 71}{space 4}-.1849582{col 84}{space 3}-.0252709
{txt}{space 29} {c |}
family#c.treat_margin_victory {c |}
{space 27}1  {c |}{col 31}{res}{space 2}-.0340463{col 43}{space 2} .3836984{col 54}{space 1}   -0.09{col 63}{space 3}0.929{col 71}{space 4}-.7872324{col 84}{space 3} .7191398
{txt}{space 29} {c |}
{space 6}family#c.margin_victory {c |}
{space 27}1  {c |}{col 31}{res}{space 2} .0401873{col 43}{space 2} .3352339{col 54}{space 1}    0.12{col 63}{space 3}0.905{col 71}{space 4}-.6178648{col 84}{space 3} .6982394
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .1403564{col 43}{space 2} .0212472{col 54}{space 1}    6.61{col 63}{space 3}0.000{col 71}{space 4} .0986488{col 84}{space 3} .1820639
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} 1.treat + 1.treat#1.family = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}donate_15any{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1642552{col 26}{space 2} .0322725{col 37}{space 1}   -5.09{col 46}{space 3}0.000{col 54}{space 4}-.2276048{col 67}{space 3}-.1009055
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,601
                                                {txt}F(7, 792)         =  {res}    11.64
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0476
                                                {txt}Root MSE          =    {res} .20465

{txt}{ralign 95:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                           b5{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}1.treat {c |}{col 31}{res}{space 2}-.0410037{col 43}{space 2}  .020527{col 54}{space 1}   -2.00{col 63}{space 3}0.046{col 71}{space 4}-.0812975{col 84}{space 3}-.0007099
{txt}{space 9}treat_margin_victory {c |}{col 31}{res}{space 2}-.1105313{col 43}{space 2} .1730135{col 54}{space 1}   -0.64{col 63}{space 3}0.523{col 71}{space 4}-.4501506{col 84}{space 3}  .229088
{txt}{space 15}margin_victory {c |}{col 31}{res}{space 2} .1811109{col 43}{space 2} .1273196{col 54}{space 1}    1.42{col 63}{space 3}0.155{col 71}{space 4}-.0688128{col 84}{space 3} .4310347
{txt}{space 21}1.family {c |}{col 31}{res}{space 2} .0559076{col 43}{space 2} .0299951{col 54}{space 1}    1.86{col 63}{space 3}0.063{col 71}{space 4}-.0029717{col 84}{space 3} .1147868
{txt}{space 29} {c |}
{space 17}treat#family {c |}
{space 25}1 1  {c |}{col 31}{res}{space 2}-.0910468{col 43}{space 2} .0329039{col 54}{space 1}   -2.77{col 63}{space 3}0.006{col 71}{space 4} -.155636{col 84}{space 3}-.0264576
{txt}{space 29} {c |}
family#c.treat_margin_victory {c |}
{space 27}1  {c |}{col 31}{res}{space 2} .0396963{col 43}{space 2} .3233996{col 54}{space 1}    0.12{col 63}{space 3}0.902{col 71}{space 4}-.5951254{col 84}{space 3} .6745179
{txt}{space 29} {c |}
{space 6}family#c.margin_victory {c |}
{space 27}1  {c |}{col 31}{res}{space 2}-.1248508{col 43}{space 2} .2917073{col 54}{space 1}   -0.43{col 63}{space 3}0.669{col 71}{space 4}-.6974617{col 84}{space 3} .4477602
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .0912884{col 43}{space 2} .0170437{col 54}{space 1}    5.36{col 63}{space 3}0.000{col 71}{space 4} .0578323{col 84}{space 3} .1247446
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} 1.treat + 1.treat#1.family = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          b5{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1320505{col 26}{space 2} .0287091{col 37}{space 1}   -4.60{col 46}{space 3}0.000{col 54}{space 4}-.1884054{col 67}{space 3}-.0756956
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         *Continue table
.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v1_donate_15any' & `fp_v1_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci1_donate_15any',`fuci1_donate_15any'] & [`flci1_b5',`fuci1_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Electoral victory $\times$ Family & `fb2_donate_15any' & `fb2_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v2_donate_15any' & `fp_v2_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci2_donate_15any',`fuci2_donate_15any'] & [`flci2_b5',`fuci2_b5']  \\
{res}{txt}
{com}.         tex & &  \\ \hline
{res}{txt}
{com}.         
.         tex Electoral victory (Family) & `fb3_donate_15any' & `fb3_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v3_donate_15any' & `fp_v3_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci3_donate_15any',`fuci3_donate_15any'] & [`flci3_b5',`fuci3_b5']  \\
{res}{txt}
{com}.         tex & & \\ \hline
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}OLS estimates of average treatment effects at cutoff. Controls include interaction of treatment with running variable and running variable. 95\% robust confidence intervals and p-values with clustering at the municipality level. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableF5.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. keep muni_code margin_victory fdonate_15any fb5
{txt}
{com}. 
. foreach var in donate_15any b5{c -(}
{txt}  2{com}.     rename  f`var' `var'
{txt}  3{com}. {c )-}
{res}{txt}
{com}. 
. gen family=1
{txt}
{com}. 
. save  "Data\cand_level_persist_fam_aux_rep.dta",replace
{txt}{p 0 4 2}
file {bf}
Data\cand_level_persist_fam_aux_rep.dta{rm}
saved
{p_end}

{com}. 
. use  "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. keep muni_code margin_victory nfdonate_15any nfb5
{txt}
{com}. 
. foreach var in donate_15any b5{c -(}
{txt}  2{com}.     rename  nf`var' `var'
{txt}  3{com}. {c )-}
{res}{txt}
{com}. 
. gen family=0
{txt}
{com}. 
. append using "Data\cand_level_persist_fam_aux_rep.dta"
{txt}
{com}. 
. 
.                 
.         gen treat=0
{txt}
{com}.         replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(1,264 real changes made)

{com}.         replace treat=. if margin_victory==.
{txt}(878 real changes made, 878 to missing)

{com}. 
.         gen treat_margin_victory=treat*margin_victory
{txt}(878 missing values generated)

{com}.         gen margin_victory_sq=margin_victory^2
{txt}(878 missing values generated)

{com}.         gen treat_margin_victory_sq=treat*margin_victory_sq
{txt}(878 missing values generated)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableF5.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableF5.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableF5.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members global parametric quadratic RD){c )-}\label{c -(}tab:donation_fam_nofam_inter_q{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c {c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor  \\ 
{res}{txt}
{com}.         tex & (1) & (2)  \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}\\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_15any b5{c -(}
{txt}  2{com}.                         
.                 quietly: regress `x' (i.treat c.treat_margin_victory_sq c.margin_victory_sq c.treat_margin_victory c.margin_victory)##i.family, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 regress `x' (i.treat c.treat_margin_victory_sq c.margin_victory_sq c.treat_margin_victory c.margin_victory)##i.family, vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`x' : di %5.3f b[1,2]
{txt} 13{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,2])
{txt} 14{com}.                 local fp_v1_`x' :di %5.3f res[4,2]
{txt} 15{com}.                 local fuci1_`x': di %5.3f res[6,2]
{txt} 16{com}.                 local flci1_`x': di %5.3f res[5,2]
{txt} 17{com}.                 
.                 local fb2_`x' : di %5.3f b[1,12]
{txt} 18{com}.                 local fse2_`x' : di %5.3f sqrt(v[1,12])
{txt} 19{com}.                 local fp_v2_`x' :di %5.3f res[4,12]
{txt} 20{com}.                 local fuci2_`x': di %5.3f res[6,12]
{txt} 21{com}.                 local flci2_`x': di %5.3f res[5,12]
{txt} 22{com}. 
.                 lincom 1.treat+ 1.treat#1.family
{txt} 23{com}.                 
.                 local fb3_`x': di %5.3f r(estimate)
{txt} 24{com}.                 local fp_v3_`x' :di %5.3f r(p)
{txt} 25{com}.                 local fuci3_`x': di %5.3f r(ub)
{txt} 26{com}.                 local flci3_`x': di %5.3f r(lb)
{txt} 27{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,601
                                                {txt}F(11, 792)        =  {res}     9.72
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0492
                                                {txt}Root MSE          =    {res} .23565

{txt}{ralign 98:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 33}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 34}{c |}{col 46}    Robust
{col 1}                    donate_15any{col 34}{c |} Coefficient{col 46}  std. err.{col 58}      t{col 66}   P>|t|{col 74}     [95% con{col 87}f. interval]
{hline 33}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25}1.treat {c |}{col 34}{res}{space 2}-.0539376{col 46}{space 2}  .034275{col 57}{space 1}   -1.57{col 66}{space 3}0.116{col 74}{space 4}-.1212181{col 87}{space 3} .0133429
{txt}{space 9}treat_margin_victory_sq {c |}{col 34}{res}{space 2} .7074192{col 46}{space 2} 2.458406{col 57}{space 1}    0.29{col 66}{space 3}0.774{col 74}{space 4}-4.118343{col 87}{space 3} 5.533182
{txt}{space 15}margin_victory_sq {c |}{col 34}{res}{space 2}-1.356426{col 46}{space 2} 2.251837{col 57}{space 1}   -0.60{col 66}{space 3}0.547{col 74}{space 4}-5.776701{col 87}{space 3} 3.063848
{txt}{space 12}treat_margin_victory {c |}{col 34}{res}{space 2}  .407932{col 46}{space 2} .6537177{col 57}{space 1}    0.62{col 66}{space 3}0.533{col 74}{space 4}-.8752922{col 87}{space 3} 1.691156
{txt}{space 18}margin_victory {c |}{col 34}{res}{space 2}-.1703285{col 46}{space 2} .5805721{col 57}{space 1}   -0.29{col 66}{space 3}0.769{col 74}{space 4}-1.309971{col 87}{space 3} .9693135
{txt}{space 24}1.family {c |}{col 34}{res}{space 2} .0710274{col 46}{space 2} .0485476{col 57}{space 1}    1.46{col 66}{space 3}0.144{col 74}{space 4}-.0242698{col 87}{space 3} .1663245
{txt}{space 32} {c |}
{space 20}treat#family {c |}
{space 28}1 1  {c |}{col 34}{res}{space 2}-.1181774{col 46}{space 2} .0536893{col 57}{space 1}   -2.20{col 66}{space 3}0.028{col 74}{space 4}-.2235675{col 87}{space 3}-.0127873
{txt}{space 32} {c |}
family#c.treat_margin_victory_sq {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-2.211874{col 46}{space 2} 3.824577{col 57}{space 1}   -0.58{col 66}{space 3}0.563{col 74}{space 4}-9.719379{col 87}{space 3} 5.295632
{txt}{space 32} {c |}
{space 6}family#c.margin_victory_sq {c |}
{space 30}1  {c |}{col 34}{res}{space 2} 3.814513{col 46}{space 2} 3.649669{col 57}{space 1}    1.05{col 66}{space 3}0.296{col 74}{space 4}-3.349655{col 87}{space 3} 10.97868
{txt}{space 32} {c |}
{space 3}family#c.treat_margin_victory {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-1.277869{col 46}{space 2} 1.045392{col 57}{space 1}   -1.22{col 66}{space 3}0.222{col 74}{space 4}-3.329936{col 87}{space 3} .7741977
{txt}{space 32} {c |}
{space 9}family#c.margin_victory {c |}
{space 30}1  {c |}{col 34}{res}{space 2}  .881191{col 46}{space 2} .9354981{col 57}{space 1}    0.94{col 66}{space 3}0.347{col 74}{space 4}-.9551579{col 87}{space 3}  2.71754
{txt}{space 32} {c |}
{space 27}_cons {c |}{col 34}{res}{space 2} .1292546{col 46}{space 2} .0291051{col 57}{space 1}    4.44{col 66}{space 3}0.000{col 74}{space 4} .0721223{col 87}{space 3} .1863869
{txt}{hline 33}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} 1.treat + 1.treat#1.family = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}donate_15any{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} -.172115{col 26}{space 2} .0433815{col 37}{space 1}   -3.97{col 46}{space 3}0.000{col 54}{space 4}-.2572713{col 67}{space 3}-.0869587
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,601
                                                {txt}F(11, 792)        =  {res}     8.59
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0483
                                                {txt}Root MSE          =    {res} .20483

{txt}{ralign 98:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 33}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 34}{c |}{col 46}    Robust
{col 1}                              b5{col 34}{c |} Coefficient{col 46}  std. err.{col 58}      t{col 66}   P>|t|{col 74}     [95% con{col 87}f. interval]
{hline 33}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25}1.treat {c |}{col 34}{res}{space 2}-.0357185{col 46}{space 2} .0274282{col 57}{space 1}   -1.30{col 66}{space 3}0.193{col 74}{space 4}-.0895591{col 87}{space 3} .0181222
{txt}{space 9}treat_margin_victory_sq {c |}{col 34}{res}{space 2} .7319343{col 46}{space 2} 1.724845{col 57}{space 1}    0.42{col 66}{space 3}0.671{col 74}{space 4}-2.653874{col 87}{space 3} 4.117743
{txt}{space 15}margin_victory_sq {c |}{col 34}{res}{space 2}-1.511927{col 46}{space 2} 1.545035{col 57}{space 1}   -0.98{col 66}{space 3}0.328{col 74}{space 4}-4.544774{col 87}{space 3}  1.52092
{txt}{space 12}treat_margin_victory {c |}{col 34}{res}{space 2} .4285834{col 46}{space 2}  .508189{col 57}{space 1}    0.84{col 66}{space 3}0.399{col 74}{space 4}-.5689732{col 87}{space 3}  1.42614
{txt}{space 18}margin_victory {c |}{col 34}{res}{space 2}-.1690073{col 46}{space 2} .4417708{col 57}{space 1}   -0.38{col 66}{space 3}0.702{col 74}{space 4}-1.036187{col 87}{space 3} .6981728
{txt}{space 24}1.family {c |}{col 34}{res}{space 2} .0746545{col 46}{space 2} .0406447{col 57}{space 1}    1.84{col 66}{space 3}0.067{col 74}{space 4}-.0051297{col 87}{space 3} .1544386
{txt}{space 32} {c |}
{space 20}treat#family {c |}
{space 28}1 1  {c |}{col 34}{res}{space 2}-.1057849{col 46}{space 2} .0432193{col 57}{space 1}   -2.45{col 66}{space 3}0.015{col 74}{space 4}-.1906229{col 87}{space 3} -.020947
{txt}{space 32} {c |}
family#c.treat_margin_victory_sq {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-1.943572{col 46}{space 2}  3.06415{col 57}{space 1}   -0.63{col 66}{space 3}0.526{col 74}{space 4}-7.958388{col 87}{space 3} 4.071243
{txt}{space 32} {c |}
{space 6}family#c.margin_victory_sq {c |}
{space 30}1  {c |}{col 34}{res}{space 2} 2.414308{col 46}{space 2} 3.087934{col 57}{space 1}    0.78{col 66}{space 3}0.435{col 74}{space 4}-3.647194{col 87}{space 3}  8.47581
{txt}{space 32} {c |}
{space 3}family#c.treat_margin_victory {c |}
{space 30}1  {c |}{col 34}{res}{space 2}-.6132116{col 46}{space 2}  .864822{col 57}{space 1}   -0.71{col 66}{space 3}0.478{col 74}{space 4}-2.310826{col 87}{space 3} 1.084403
{txt}{space 32} {c |}
{space 9}family#c.margin_victory {c |}
{space 30}1  {c |}{col 34}{res}{space 2} .4186944{col 46}{space 2} .7924162{col 57}{space 1}    0.53{col 66}{space 3}0.597{col 74}{space 4} -1.13679{col 87}{space 3} 1.974179
{txt}{space 32} {c |}
{space 27}_cons {c |}{col 34}{res}{space 2}  .078914{col 46}{space 2}  .023674{col 57}{space 1}    3.33{col 66}{space 3}0.001{col 74}{space 4} .0324428{col 87}{space 3} .1253852
{txt}{hline 33}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} 1.treat + 1.treat#1.family = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          b5{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1415034{col 26}{space 2} .0385783{col 37}{space 1}   -3.67{col 46}{space 3}0.000{col 54}{space 4}-.2172311{col 67}{space 3}-.0657756
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         *Continue table
.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v1_donate_15any' & `fp_v1_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci1_donate_15any',`fuci1_donate_15any'] & [`flci1_b5',`fuci1_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Electoral victory $\times$ Family & `fb2_donate_15any' & `fb2_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v2_donate_15any' & `fp_v2_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci2_donate_15any',`fuci2_donate_15any'] & [`flci2_b5',`fuci2_b5']  \\
{res}{txt}
{com}.         tex & &  \\ \hline
{res}{txt}
{com}.         
.         tex Electoral victory (Family) & `fb3_donate_15any' & `fb3_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v3_donate_15any' & `fp_v3_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci3_donate_15any',`fuci3_donate_15any'] & [`flci3_b5',`fuci3_b5']  \\
{res}{txt}
{com}.         tex & &  \\ \hline
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' \\
{res}{txt}
{com}.         tex R-squared & `fR2_donate_15any' & `fR2_b5'  \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}OLS estimates of average treatment effects at the cutoff for family and non- family donors. Controls include the interaction of the treatment with running variable and running variable, interaction of the treatment with the squared running variable, the running variable squared, interaction of family dummy with all previous variables, and family dummy. P-values and 95\% robust confidence intervals with clustering at the municipality level.  
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG1.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.    
{txt}(1,904 real changes made, 1,904 to missing)

{com}. gen treat_margin_victory=treat*margin_victory
{txt}(1,904 missing values generated)

{com}.         
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0   
{txt}(227 real changes made, 227 to missing)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (donor-level){c )-}\label{c -(}tab:donations_d{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:& Any race & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly: regress `var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `var' if e(sample)
{txt}  4{com}.                         local mean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`var' : di %5.3f r(sd) 
{txt}  6{com}.                 
.                 *Regressions
.                 rdrobust `var' margin_victory, p(1) vce(cluster muni_code) 
{txt}  7{com}.                 
.                 *Local's for the table
.                 local bw_`var' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local ser_`var' = round(`e(se_tau_rb)',0.001)
{txt}  9{com}.                 local Neff_`var' = `e(N_h_l)'+`e(N_h_r)'
{txt} 10{com}.                 local N_`var' = `e(N)'
{txt} 11{com}.                 local poly_`var' = `e(p)'
{txt} 12{com}.                 local beta1_`var' : di %5.3f `e(tau_cl)'
{txt} 13{com}.                 local beta2_`var' : di %5.3f `e(tau_bc)'
{txt} 14{com}. 
.                 *Confidence intervals
.                         local ser1_`var' : di %5.3f `e(ci_l_rb)'
{txt} 15{com}.                         local ser2_`var' : di %5.3f `e(ci_r_rb)'
{txt} 16{com}.                         
. /* HERE*/       local em1_`var' = (`beta1_`var''/`mean_`var'')*100 
{txt} 17{com}.                         local em1_`var' : di %5.2f `em1_`var''
{txt} 18{com}.                         
.                 *P-values
.                 local pval2_`var' : di %5.3f `e(pv_rb)'
{txt} 19{com}.                 scalar pval2_`var' = e(pv_rb)
{txt} 20{com}.                 
.                 regress `var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 21{com}. 
.                 local N_`var' : di %5.0f e(N)
{txt} 22{com}.                 local R2_`var' : di %5.3f e(r2)
{txt} 23{com}. 
.                 matrix b = e(b)
{txt} 24{com}.                 matrix v = e(V)
{txt} 25{com}.                 matrix res=r(table)
{txt} 26{com}.                 
.                 local b1_`var' : di %5.3f b[1,1]
{txt} 27{com}.                 local se1_`var' : di %5.3f sqrt(v[1,1])
{txt} 28{com}.                 local p_v_`var' :di %5.3f res[4,1]
{txt} 29{com}.                 local uci_`var': di %5.3f res[6,1]
{txt} 30{com}.                 local lci_`var': di %5.3f res[5,1]
{txt} 31{com}.         {c )-}       
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      6627
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     2614{col 34}     4013{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}     1530{col 34}     2087{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.136{col 34}    0.136
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.579{col 34}    0.579
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      516{col 34}      632
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      498

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06514{col 33} .02689{col 43}-2.4226{col 52}0.015{col 60}-.117848{col 73}-.012441
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.9931{col 52}0.046{col 60}-.129386{col 73}-.001086
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     6,627
                                                {txt}F(3, 792)         =  {res}    15.26
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0129
                                                {txt}Root MSE          =    {res} .29211

{txt}{ralign 86:(Std. err. adjusted for {res:793} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}        donate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0890261{col 34}{space 2} .0177975{col 45}{space 1}   -5.00{col 54}{space 3}0.000{col 62}{space 4}-.1239619{col 75}{space 3}-.0540903
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .2215691{col 34}{space 2} .1505611{col 45}{space 1}    1.47{col 54}{space 3}0.142{col 62}{space 4}-.0739769{col 75}{space 3} .5171151
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0381315{col 34}{space 2} .1307193{col 45}{space 1}    0.29{col 54}{space 3}0.771{col 62}{space 4}-.2184657{col 75}{space 3} .2947287
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1358078{col 34}{space 2} .0154604{col 45}{space 1}    8.78{col 54}{space 3}0.000{col 62}{space 4} .1054595{col 75}{space 3}  .166156
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      6416
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     2521{col 34}     3895{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}     1349{col 34}     1674{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.585{col 34}    0.585
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      509{col 34}      628
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      377{col 34}      445

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05988{col 33} .02832{col 43}-2.1148{col 52}0.034{col 60}-.115378{col 73}-.004384
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.9168{col 52}0.055{col 60}-.132622{col 73} .001477
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     6,416
                                                {txt}F(3, 786)         =  {res}    12.64
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0143
                                                {txt}Root MSE          =    {res} .24618

{txt}{ralign 86:(Std. err. adjusted for {res:787} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                  b5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} -.080794{col 34}{space 2} .0166966{col 45}{space 1}   -4.84{col 54}{space 3}0.000{col 62}{space 4}-.1135692{col 75}{space 3}-.0480189
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .0223691{col 34}{space 2} .1368293{col 45}{space 1}    0.16{col 54}{space 3}0.870{col 62}{space 4} -.246225{col 75}{space 3} .2909631
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1214923{col 34}{space 2} .1257792{col 45}{space 1}    0.97{col 54}{space 3}0.334{col 62}{space 4}-.1254106{col 75}{space 3} .3683952
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1104603{col 34}{space 2} .0149934{col 45}{space 1}    7.37{col 54}{space 3}0.000{col 62}{space 4} .0810284{col 75}{space 3} .1398922
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}&\\
{res}{txt}
{com}.         tex Electoral victory & `beta1_donate_15any' & `beta1_b5' & `beta1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `pval2_donate_15any' & `pval2_b5' & `pval2_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`ser1_donate_15any',`ser2_donate_15any'] & [`ser1_b5',`ser2_b5'] & [`ser1_b2b',`ser2_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}&\\
{res}{txt}
{com}.         tex Electoral victory & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `Neff_donate_15any' & `Neff_b5' & `Neff_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `em1_donate_15any' & `em1_b5' & `em1_b2b' \\
.         tex Bandwidth & `bw_donate_15any' & `bw_b5' & `bw_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. 95\% robust confidence intervals and robust p-values with clustering at the municipality level are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(2,365 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(6,166 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(2,365 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(6,166 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(6,166 missing values generated)

{com}. gen fgot_above_ext = got_above_ext if family==1
{txt}(6,166 missing values generated)

{com}. 
. 
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(370 real changes made, 370 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG2.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on benefits to donors (donor-level){c )-}\label{c -(}tab:table_benefits_d{c )-}
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c{c )-} \hline
{res}{txt}
{com}.         tex Outcome:& \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Total contracts{c )-}&\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Receive contract{c )-}&Receive contract& Runs in 2015\\
{res}{txt}
{com}.         tex &  \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} &\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} & (outside)& \\
{res}{txt}
{com}.         tex & Non-Family &Family & Non-Family &Family  & Family &Family \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4)& (5) & (6)\\ \hline
{res}{txt}
{com}.         tex & & & & & &\\
{res}{txt}
{com}.         
.         
.         *Model 1
.         foreach x in total_cont_num_d contract{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum nf`x' if e(sample)
{txt}  4{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 rdrobust nf`x' margin_victory , vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local nfbw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local nfNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local nfN_`x' = `e(N)'
{txt} 10{com}.                 local nfbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local nfbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local nfser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local nfser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local nfem1_`x' = (`nfbeta1_`x''/`nfmean_`x'')*100 
{txt} 15{com}.                         local nfem1_`x' : di %5.2f `nfem1_`x''
{txt} 16{com}.                         
.                 *P-values
.                 local nfpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar nfpval2_`x' = e(pv_rb)
{txt} 18{com}.                 
.                                 regress nf`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt} 20{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 25{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 27{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 28{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 29{com}.                 
.         
.         {c )-}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      4866
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1879{col 34}     2987{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}     1286{col 34}     1777{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.643{col 34}    0.643
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      370{col 34}      451
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      404

Outcome: nftotal_cont_num_d. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} 1.1027{col 33}  .3857{col 43}2.8590{col 52}0.004{col 60} .346775{col 73}  1.8587
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}2.4754{col 52}0.013{col 60} .236292{col 73} 2.03326
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     4,866
                                                {txt}F(3, 614)         =  {res}     9.36
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0066
                                                {txt}Root MSE          =    {res} 4.0923

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}  nftotal_cont_num_d{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .8484493{col 34}{space 2} .2133281{col 45}{space 1}    3.98{col 54}{space 3}0.000{col 62}{space 4} .4295081{col 75}{space 3} 1.267391
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-1.950745{col 34}{space 2} 2.023062{col 45}{space 1}   -0.96{col 54}{space 3}0.335{col 62}{space 4}-5.923705{col 75}{space 3} 2.022215
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.1050807{col 34}{space 2} .7787274{col 45}{space 1}   -0.13{col 54}{space 3}0.893{col 62}{space 4}-1.634373{col 75}{space 3} 1.424211
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .2868589{col 34}{space 2} .0660348{col 45}{space 1}    4.34{col 54}{space 3}0.000{col 62}{space 4} .1571774{col 75}{space 3} .4165403
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      4866
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1879{col 34}     2987{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}     1105{col 34}     1514{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.609{col 34}    0.609
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      370{col 34}      451
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      283{col 34}      342

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06993{col 33} .03865{col 43}1.8095{col 52}0.070{col 60}-.005817{col 73} .145677
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}1.3399{col 52}0.180{col 60}-.028849{col 73} .153523
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     4,866
                                                {txt}F(3, 614)         =  {res}    13.83
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0170
                                                {txt}Root MSE          =    {res} .30824

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}          nfcontract{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .0963269{col 34}{space 2}  .020701{col 45}{space 1}    4.65{col 54}{space 3}0.000{col 62}{space 4} .0556735{col 75}{space 3} .1369802
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.2967707{col 34}{space 2} .2042597{col 45}{space 1}   -1.45{col 54}{space 3}0.147{col 62}{space 4} -.697903{col 75}{space 3} .1043616
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0616874{col 34}{space 2} .1327245{col 45}{space 1}    0.46{col 54}{space 3}0.642{col 62}{space 4}-.1989617{col 75}{space 3} .3223365
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0651347{col 34}{space 2} .0135437{col 45}{space 1}    4.81{col 54}{space 3}0.000{col 62}{space 4} .0385371{col 75}{space 3} .0917323
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 
. 
.         foreach x in  total_cont_num_d contract got_above_ext runs_any{c -(}
{txt}  2{com}.         
.                 *Family
.                 *Regressions
.                 quietly: regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 rdrobust f`x' margin_victory , vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local fbw_`x' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local fNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local fN_`x' = `e(N)'
{txt} 10{com}.                 local fbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local fbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local fser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local fser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local fem1_`x' = (`fbeta1_`x''/`fmean_`x'')*100 
{txt} 15{com}.                         local fem1_`x' : di %5.2f `fem1_`x''
{txt} 16{com}.                         
.                 *P-values
.                 local fpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar fpval2_`x' = e(pv_rb)
{txt} 18{com}.                 
.                                 regress f`x' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt} 20{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 25{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 27{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 28{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 29{com}. 
.         {c )-}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1761
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      735{col 34}     1026{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      305{col 34}      397{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.436{col 34}    0.436
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      339{col 34}      439
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      252{col 34}      307

Outcome: ftotal_cont_num_d. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00058{col 33} .00068{col 43}0.8566{col 52}0.392{col 60}-.000749{col 73} .001913
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}0.6857{col 52}0.493{col 60}-.002072{col 73} .004303
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,761
                                                {txt}F(3, 612)         =  {res}     0.77
                                                {txt}Prob > F          = {res}    0.5093
                                                {txt}R-squared         = {res}    0.0041
                                                {txt}Root MSE          =    {res} .11401

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}   ftotal_cont_num_d{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .0050414{col 34}{space 2} .0115156{col 45}{space 1}    0.44{col 54}{space 3}0.662{col 62}{space 4}-.0175734{col 75}{space 3} .0276562
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}  .147148{col 34}{space 2} .1757284{col 45}{space 1}    0.84{col 54}{space 3}0.403{col 62}{space 4}-.1979558{col 75}{space 3} .4922518
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.1560457{col 34}{space 2} .1753055{col 45}{space 1}   -0.89{col 54}{space 3}0.374{col 62}{space 4}-.5003191{col 75}{space 3} .1882276
{txt}{space 15}_cons {c |}{col 22}{res}{space 2}-.0013551{col 34}{space 2} .0112737{col 45}{space 1}   -0.12{col 54}{space 3}0.904{col 62}{space 4} -.023495{col 75}{space 3} .0207848
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1761
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      735{col 34}     1026{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      309{col 34}      397{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.416{col 34}    0.416
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      339{col 34}      439
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      315

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00063{col 33} .00072{col 43}0.8767{col 52}0.381{col 60}-.000778{col 73} .002038
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}0.9683{col 52}0.333{col 60}-.001179{col 73}  .00348
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,761
                                                {txt}F(3, 612)         =  {res}     0.57
                                                {txt}Prob > F          = {res}    0.6320
                                                {txt}R-squared         = {res}    0.0015
                                                {txt}Root MSE          =    {res} .06295

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           fcontract{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} .0023624{col 34}{space 2} .0048098{col 45}{space 1}    0.49{col 54}{space 3}0.623{col 62}{space 4}-.0070833{col 75}{space 3}  .011808
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .0436075{col 34}{space 2} .0603833{col 45}{space 1}    0.72{col 54}{space 3}0.470{col 62}{space 4}-.0749761{col 75}{space 3} .1621911
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.0525053{col 34}{space 2} .0591007{col 45}{space 1}   -0.89{col 54}{space 3}0.375{col 62}{space 4}  -.16857{col 75}{space 3} .0635594
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0013239{col 34}{space 2} .0042045{col 45}{space 1}    0.31{col 54}{space 3}0.753{col 62}{space 4} -.006933{col 75}{space 3} .0095808
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1761
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      735{col 34}     1026{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      441{col 34}      609{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.085{col 34}    0.085
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.140{col 34}    0.140
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.607{col 34}    0.607
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      339{col 34}      439
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      287{col 34}      355

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03659{col 33} .03671{col 43}-0.9967{col 52}0.319{col 60}-.108535{col 73}  .03536
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.9413{col 52}0.347{col 60}-.124966{col 73} .043876
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,761
                                                {txt}F(3, 612)         =  {res}     3.49
                                                {txt}Prob > F          = {res}    0.0155
                                                {txt}R-squared         = {res}    0.0057
                                                {txt}Root MSE          =    {res} .29248

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}      fgot_above_ext{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0292818{col 34}{space 2} .0226072{col 45}{space 1}   -1.30{col 54}{space 3}0.196{col 62}{space 4}-.0736788{col 75}{space 3} .0151153
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .1757095{col 34}{space 2} .2068443{col 45}{space 1}    0.85{col 54}{space 3}0.396{col 62}{space 4}-.2305013{col 75}{space 3} .5819203
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.1736763{col 34}{space 2} .1718801{col 45}{space 1}   -1.01{col 54}{space 3}0.313{col 62}{space 4}-.5112227{col 75}{space 3} .1638701
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1061056{col 34}{space 2} .0180841{col 45}{space 1}    5.87{col 54}{space 3}0.000{col 62}{space 4} .0705912{col 75}{space 3}   .14162
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1761
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      735{col 34}     1026{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      368{col 34}      482{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.577{col 34}    0.577
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      339{col 34}      439
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      250{col 34}      306

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00949{col 33} .01232{col 43}-0.7704{col 52}0.441{col 60}-.033631{col 73} .014653
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.7944{col 52}0.427{col 60}-.038831{col 73} .016432
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,761
                                                {txt}F(3, 612)         =  {res}     1.03
                                                {txt}Prob > F          = {res}    0.3797
                                                {txt}R-squared         = {res}    0.0021
                                                {txt}Root MSE          =    {res} .11831

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}           fruns_any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}  .006922{col 34}{space 2} .0089597{col 45}{space 1}    0.77{col 54}{space 3}0.440{col 62}{space 4}-.0106735{col 75}{space 3} .0245176
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .1627202{col 34}{space 2} .1022489{col 45}{space 1}    1.59{col 54}{space 3}0.112{col 62}{space 4}-.0380811{col 75}{space 3} .3635216
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2}-.1067182{col 34}{space 2} .0853545{col 45}{space 1}   -1.25{col 54}{space 3}0.212{col 62}{space 4}-.2743415{col 75}{space 3} .0609051
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0038745{col 34}{space 2} .0068124{col 45}{space 1}    0.57{col 54}{space 3}0.570{col 62}{space 4} -.009504{col 75}{space 3}  .017253
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 
.         
. 
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfbeta1_total_cont_num_d' &  `fbeta1_total_cont_num_d'& `nfbeta1_contract' & `fbeta1_contract' & `fbeta1_got_above_ext' & `fbeta1_runs_any' \\
{res}{txt}
{com}.         
.         tex \ \ \ \ Robust p-value & `nfpval2_total_cont_num_d' &  `fpval2_total_cont_num_d' & `nfpval2_contract' & `fpval2_contract' & `fpval2_got_above_ext' & `fpval2_runs_any' \\
{res}{txt}
{com}.         
.         
.         
.         tex \ \ \ \ CI 95\%  & [`nfser1_total_cont_num_d',`nfser2_total_cont_num_d'] & [`fser1_total_cont_num_d',`fser2_total_cont_num_d'] &  [`nfser1_contract',`nfser2_contract'] & [`fser1_contract',`fser2_contract'] & [`fser1_got_above_ext',`fser2_got_above_ext'] & [`fser1_runs_any',`fser2_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfb1_total_cont_num_d' &  `fb1_total_cont_num_d'& `nfb1_contract' & `fb1_contract' & `fb1_got_above_ext' & `fb1_runs_any' \\
{res}{txt}
{com}.         
.         tex \ \ \ \  p-value & `nfp_v_total_cont_num_d' &  `fp_v_total_cont_num_d' & `nfp_v_contract' & `fp_v_contract' & `fp_v_got_above_ext' & `fp_v_runs_any' \\
{res}{txt}
{com}.         
.         
.         
.         tex \ \ \ \ CI 95\%  & [`nflci_total_cont_num_d',`nflci_total_cont_num_d'] & [`flci_total_cont_num_d',`fuci_total_cont_num_d'] &  [`nflci_contract',`nfuci_contract'] & [`flci_contract',`fuci_contract'] & [`flci_got_above_ext',`fuci_got_above_ext'] & [`flci_runs_any',`fuci_runs_any']\\
{res}{txt}
{com}.         tex & & & \\    
{res}{txt}
{com}.         
.         tex Observations &`nfN_total_cont_num_d' &  `fN_total_cont_num_d' & `nfN_contract'& `fN_contract' & `fN_got_above_ext' & `fN_runs_any' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `nfNeff_total_cont_num_d' & `fNeff_total_cont_num_d' & `nfNeff_contract'&  `fNeff_contract' & `fNeff_got_above_ext' & `fNeff_runs_any' \\
{res}{txt}
{com}.         tex Mean & `nfmean_total_cont_num_d' &`fmean_total_cont_num_d'  &  `nfmean_contract' & `fmean_contract' & `fmean_got_above_ext' & `fmean_runs_any' \\
{res}{txt}
{com}.         tex Bandwidth & `nfbw_total_cont_num_d' &  `fbw_total_cont_num_d' &`nfbw_contract' & `fbw_contract' & `fbw_got_above_ext' & `fbw_runs_any' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level and 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. The parametric linear model specification includes interaction of the treatment with running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. 
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(1,906 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(5,091 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(1,906 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(5,091 missing values generated)

{com}. gen nfruns_any = runs_any if family==0
{txt}(1,906 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(5,091 missing values generated)

{com}. gen nfdonate_15any = donate_15any if family==0
{txt}(1,906 missing values generated)

{com}. gen fdonate_15any = donate_15any if family==1
{txt}(5,091 missing values generated)

{com}. gen nfb5 = b5 if family==0
{txt}(2,097 missing values generated)

{com}. gen fb5 = b5 if family==1
{txt}(5,127 missing values generated)

{com}. 
. 
. 
. keep if rank==1|rank==2
{txt}(0 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(0 real changes made)

{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(370 real changes made, 370 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG3.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members, donor-level){c )-}\label{c -(}tab:donation_fam_nofam_d{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor & b2 \\ 
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}&\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.         
. 
.                 *Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly: regress f`var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`var' if e(sample)
{txt}  4{com}.                         local fmean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`var' : di %5.3f r(sd) 
{txt}  6{com}.                         
.                 rdrobust f`var' margin_victory ,  vce(cluster muni_code)
{txt}  7{com}. 
.                 *Local's for the table
.                 local fbw_`var' : di %5.2f `e(h_l)'
{txt}  8{com}.                 local fNeff_`var' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local fN_`var' = `e(N)'
{txt} 10{com}.                 local fbeta1_`var' : di %5.3f `e(tau_cl)'
{txt} 11{com}.                 local fbeta2_`var' : di %5.3f `e(tau_bc)'
{txt} 12{com}. 
.                 *Confidence intervals
.                         local fser1_`var' : di %5.3f `e(ci_l_rb)'
{txt} 13{com}.                         local fser2_`var' : di %5.3f `e(ci_r_rb)'
{txt} 14{com}.                         
. /* HERE*/       local fem1_`var' = (`fbeta1_`var''/`fmean_`var'')*100 
{txt} 15{com}.                         local fem1_`var' : di %5.2f `fem1_`var''
{txt} 16{com}.                         
.                 *P-values
.                 local fpval2_`var' : di %5.3f `e(pv_rb)'
{txt} 17{com}.                 scalar fpval2_`var' = e(pv_rb)
{txt} 18{com}.         
. regress f`var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 19{com}. 
.                 local fN_`var' : di %5.0f e(N)
{txt} 20{com}.                 local fR2_`var' : di %5.3f e(r2)
{txt} 21{com}. 
.                 matrix b = e(b)
{txt} 22{com}.                 matrix v = e(V)
{txt} 23{com}.                 matrix res=r(table)
{txt} 24{com}.                 
.                 local fb1_`var' : di %5.3f b[1,1]
{txt} 25{com}.                 local fse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 26{com}.                 local fp_v_`var' :di %5.3f res[4,1]
{txt} 27{com}.                 local fuci_`var': di %5.3f res[6,1]
{txt} 28{com}.                 local flci_`var': di %5.3f res[5,1]
{txt} 29{com}. 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly: regress nf`var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 30{com}.                 quietly sum nf`var' if e(sample)
{txt} 31{com}.                         local nfmean_`var' : di %5.3f r(mean)
{txt} 32{com}.                         local sd_`var' : di %5.3f r(sd) 
{txt} 33{com}. 
.                 rdrobust nf`var' margin_victory ,  vce(cluster muni_code)
{txt} 34{com}. 
.                 *Local's for the table
.                 local nfbw_`var' : di %5.2f `e(h_l)'
{txt} 35{com}.                 local nfNeff_`var' = `e(N_h_l)'+`e(N_h_r)'
{txt} 36{com}.                 local nfN_`var' = `e(N)'
{txt} 37{com}.                 local nfbeta1_`var' : di %5.3f `e(tau_cl)'
{txt} 38{com}.                 local nfbeta2_`var' : di %5.3f `e(tau_bc)'
{txt} 39{com}. 
.                 *Confidence intervals
.                         local nfser1_`var' : di %5.3f `e(ci_l_rb)'
{txt} 40{com}.                         local nfser2_`var' : di %5.3f `e(ci_r_rb)'
{txt} 41{com}.                         
. /* HERE*/       local nfem1_`var' = (`nfbeta1_`var''/`nfmean_`var'')*100 
{txt} 42{com}.                         local nfem1_`var' : di %5.2f `nfem1_`var''
{txt} 43{com}.                         
.                 *P-values
.                 local nfpval2_`var' : di %5.3f `e(pv_rb)'
{txt} 44{com}.                 scalar nfpval2_`var' = e(pv_rb)
{txt} 45{com}.                 
.                 regress nf`var' treat treat_margin_victory margin_victory , vce(cluster muni_code)
{txt} 46{com}. 
.                 local nfN_`var' : di %5.0f e(N)
{txt} 47{com}.                 local nfR2_`var' : di %5.3f e(r2)
{txt} 48{com}. 
.                 matrix b = e(b)
{txt} 49{com}.                 matrix v = e(V)
{txt} 50{com}.                 matrix res=r(table)
{txt} 51{com}.                 
.                 local nfb1_`var' : di %5.3f b[1,1]
{txt} 52{com}.                 local nfse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 53{com}.                 local nfp_v_`var' :di %5.3f res[4,1]
{txt} 54{com}.                 local nfuci_`var': di %5.3f res[6,1]
{txt} 55{com}.                 local nflci_`var': di %5.3f res[5,1]
{txt} 56{com}.         {c )-}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1761
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      735{col 34}     1026{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      392{col 34}      511{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.636{col 34}    0.636
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      339{col 34}      439
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      304

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1653{col 33} .05557{col 43}-2.9744{col 52}0.003{col 60}-.274222{col 73}-.056376
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-2.5616{col 52}0.010{col 60}-.301515{col 73}-.040119
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,761
                                                {txt}F(3, 612)         =  {res}    19.91
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0596
                                                {txt}Root MSE          =    {res} .27745

{txt}{ralign 86:(Std. err. adjusted for {res:613} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}       fdonate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.1557765{col 34}{space 2} .0319091{col 45}{space 1}   -4.88{col 54}{space 3}0.000{col 62}{space 4}-.2184412{col 75}{space 3}-.0931118
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .1617636{col 34}{space 2} .3448997{col 45}{space 1}    0.47{col 54}{space 3}0.639{col 62}{space 4}-.5155669{col 75}{space 3}  .839094
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0102232{col 34}{space 2}  .284422{col 45}{space 1}    0.04{col 54}{space 3}0.971{col 62}{space 4}-.5483384{col 75}{space 3} .5687848
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1722304{col 34}{space 2} .0279055{col 45}{space 1}    6.17{col 54}{space 3}0.000{col 62}{space 4} .1174282{col 75}{space 3} .2270327
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      4866
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1879{col 34}     2987{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}     1070{col 34}     1360{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.562{col 34}    0.562
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      370{col 34}      451
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      287{col 34}      345

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03485{col 33} .03069{col 43}-1.1355{col 52}0.256{col 60}-.094999{col 73} .025301
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.9817{col 52}0.326{col 60}-.109994{col 73} .036578
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     4,866
                                                {txt}F(3, 614)         =  {res}     4.47
                                                {txt}Prob > F          = {res}    0.0041
                                                {txt}R-squared         = {res}    0.0053
                                                {txt}Root MSE          =    {res} .29613

{txt}{ralign 86:(Std. err. adjusted for {res:615} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}      nfdonate_15any{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0610346{col 34}{space 2} .0210992{col 45}{space 1}   -2.89{col 54}{space 3}0.004{col 62}{space 4}  -.10247{col 75}{space 3}-.0195992
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .2216602{col 34}{space 2} .1787979{col 45}{space 1}    1.24{col 54}{space 3}0.216{col 62}{space 4}-.1294694{col 75}{space 3} .5727897
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0387026{col 34}{space 2} .1403428{col 45}{space 1}    0.28{col 54}{space 3}0.783{col 62}{space 4}-.2369075{col 75}{space 3} .3143127
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1207505{col 34}{space 2} .0184079{col 45}{space 1}    6.56{col 54}{space 3}0.000{col 62}{space 4} .0846004{col 75}{space 3} .1569005
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1729
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      719{col 34}     1010{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      383{col 34}      510{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.629{col 34}    0.629
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      333{col 34}      437
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      306

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16266{col 33}  .0526{col 43}-3.0927{col 52}0.002{col 60}-.265746{col 73}-.059576
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-2.7120{col 52}0.007{col 60}-.293671{col 73}-.047271
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     1,729
                                                {txt}F(3, 607)         =  {res}    20.70
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0678
                                                {txt}Root MSE          =    {res} .25126

{txt}{ralign 86:(Std. err. adjusted for {res:608} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                 fb5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2} -.137553{col 34}{space 2} .0285213{col 45}{space 1}   -4.82{col 54}{space 3}0.000{col 62}{space 4}-.1935653{col 75}{space 3}-.0815406
{txt}treat_margin_victory {c |}{col 22}{res}{space 2}-.1020488{col 34}{space 2} .2901897{col 45}{space 1}   -0.35{col 54}{space 3}0.725{col 62}{space 4}-.6719466{col 75}{space 3}  .467849
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .0554845{col 34}{space 2} .2854762{col 45}{space 1}    0.19{col 54}{space 3}0.846{col 62}{space 4}-.5051564{col 75}{space 3} .6161255
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .1573313{col 34}{space 2} .0275848{col 45}{space 1}    5.70{col 54}{space 3}0.000{col 62}{space 4} .1031581{col 75}{space 3} .2115044
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{err}Mass points detected in the running variable.
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      4687
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1802{col 34}     2885{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      797{col 34}      979{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.055{col 34}    0.055
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.529{col 34}    0.529
{txt}{ralign 18:Unique obs}{col 19} {c |} {col 21}{res}      363{col 34}      447
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      236{col 34}      282

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04605{col 33} .03388{col 43}-1.3591{col 52}0.174{col 60}-.112462{col 73} .020358
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.3961{col 52}0.163{col 60}-.133251{col 73} .022386
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
Estimates adjusted for mass points in the running variable.

Linear regression                               Number of obs     = {res}     4,687
                                                {txt}F(3, 608)         =  {res}     3.46
                                                {txt}Prob > F          = {res}    0.0163
                                                {txt}R-squared         = {res}    0.0053
                                                {txt}Root MSE          =    {res}  .2427

{txt}{ralign 86:(Std. err. adjusted for {res:609} clusters in {res:muni_code})}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                nfb5{col 22}{c |} Coefficient{col 34}  std. err.{col 46}      t{col 54}   P>|t|{col 62}     [95% con{col 75}f. interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat {c |}{col 22}{res}{space 2}-.0557387{col 34}{space 2} .0188269{col 45}{space 1}   -2.96{col 54}{space 3}0.003{col 62}{space 4}-.0927124{col 75}{space 3}-.0187651
{txt}treat_margin_victory {c |}{col 22}{res}{space 2} .0512444{col 34}{space 2}  .158244{col 45}{space 1}    0.32{col 54}{space 3}0.746{col 62}{space 4}-.2595268{col 75}{space 3} .3620156
{txt}{space 6}margin_victory {c |}{col 22}{res}{space 2} .1328285{col 34}{space 2} .1252157{col 45}{space 1}    1.06{col 54}{space 3}0.289{col 62}{space 4}-.1130794{col 75}{space 3} .3787363
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .0906114{col 34}{space 2} .0171279{col 45}{space 1}    5.29{col 54}{space 3}0.000{col 62}{space 4} .0569742{col 75}{space 3} .1242485
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. 
. 
.                 
. 
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `fbeta1_donate_15any' & `fbeta1_b5' & `fbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fpval2_donate_15any' & `fpval2_b5' & `fpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`fser1_donate_15any',`fser2_donate_15any'] & [`fser1_b5',`fser2_b5'] & [`fser1_b3',`fser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.                 tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.                 tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v_donate_15any' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_15any',`fuci_donate_15any'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         
.         tex Observations & `fN_donate_15any' & `fN_b5' & `fN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `fNeff_donate_15any' & `fNeff_b5' & `fNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' & `fmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `fbw_donate_15any' & `fbw_b5' & `fbw_b3' \\ 
{res}{txt}
{com}.         
.         tex & & & \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}. 
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfbeta1_donate_15any' & `nfbeta1_b5' & `nfbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfpval2_donate_15any' & `nfpval2_b5' & `nfpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nfser1_donate_15any',`nfser2_donate_15any'] & [`nfser1_b5',`nfser2_b5'] & [`nfser1_b3',`nfser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfb1_donate_15any' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfp_v_donate_15any' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_15any',`nfuci_donate_15any'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_15any' & `nfN_b5' & `nfN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `nfNeff_donate_15any' & `nfNeff_b5' & `nfNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_15any' & `nfmean_b5' & `nfmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `nfbw_donate_15any' & `nfbw_b5' & `nfbw_b3' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level and 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with the running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG4.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(1,904 real changes made, 1,904 to missing)

{com}. 
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG4.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG4.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG4.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (donor-level){c )-}\label{c -(}tab:donations_d_ols{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.                 
.                 *No Family
.                 *Regressions
.                 quietly: regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim ,vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `var' if e(sample)
{txt}  4{com}.                         local mean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`var' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim ,vce(cluster muni_code)
{txt}  7{com}. 
.                 local N_`var' : di %5.0f e(N)
{txt}  8{com}. 
.                 matrix b = e(b)
{txt}  9{com}.                 matrix v = e(V)
{txt} 10{com}.                 matrix res=r(table)
{txt} 11{com}.                 
.                 local b1_`var' : di %5.3f b[1,1]
{txt} 12{com}.                 local se1_`var' : di %5.3f sqrt(v[1,1])
{txt} 13{com}.                 local p_v_`var' :di %5.3f res[4,1]
{txt} 14{com}.                 local uci_`var': di %5.3f res[6,1]
{txt} 15{com}.                 local lci_`var': di %5.3f res[5,1]
{txt} 16{com}.                 
.                 areg `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 17{com}. 
.                 local Nf_`var' : di %5.0f e(N)
{txt} 18{com}. 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local b1f_`var' : di %5.3f bf[1,1]
{txt} 22{com}.                 local se1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local p_vf_`var' :di %5.3f resf[4,1]
{txt} 24{com}.                 local ucif_`var': di %5.3f resf[6,1]
{txt} 25{com}.                 local lcif_`var': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     4,863
                                                {txt}F(11, 613)        =  {res}     5.54
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0224
                                                {txt}Root MSE          =    {res} .29362

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.029989{col 30}{space 2}  .015312{col 41}{space 1}   -1.96{col 50}{space 3}0.051{col 58}{space 4}-.0600593{col 71}{space 3} .0000812
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0212118{col 30}{space 2} .0308781{col 41}{space 1}    0.69{col 50}{space 3}0.492{col 58}{space 4}-.0394279{col 71}{space 3} .0818514
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .4085353{col 30}{space 2} .3697783{col 41}{space 1}    1.10{col 50}{space 3}0.270{col 58}{space 4}-.3176506{col 71}{space 3} 1.134721
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0267134{col 30}{space 2} .0260204{col 41}{space 1}   -1.03{col 50}{space 3}0.305{col 58}{space 4}-.0778132{col 71}{space 3} .0243865
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0106654{col 30}{space 2} .0065656{col 41}{space 1}   -1.62{col 50}{space 3}0.105{col 58}{space 4}-.0235592{col 71}{space 3} .0022284
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0072994{col 30}{space 2} .0171118{col 41}{space 1}    0.43{col 50}{space 3}0.670{col 58}{space 4}-.0263055{col 71}{space 3} .0409043
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0107407{col 30}{space 2} .0126052{col 41}{space 1}    0.85{col 50}{space 3}0.394{col 58}{space 4}-.0140139{col 71}{space 3} .0354954
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0010252{col 30}{space 2} .0012449{col 41}{space 1}    0.82{col 50}{space 3}0.411{col 58}{space 4}-.0014196{col 71}{space 3} .0034699
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0476154{col 30}{space 2}  .008686{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4} .0305574{col 71}{space 3} .0646734
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0236163{col 30}{space 2} .0500444{col 41}{space 1}   -0.47{col 50}{space 3}0.637{col 58}{space 4}-.1218955{col 71}{space 3} .0746629
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.048103{col 30}{space 2} .0236346{col 41}{space 1}   -2.04{col 50}{space 3}0.042{col 58}{space 4}-.0945176{col 71}{space 3}-.0016884
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0502702{col 30}{space 2}  .029131{col 41}{space 1}    1.73{col 50}{space 3}0.085{col 58}{space 4}-.0069384{col 71}{space 3} .1074788
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,863}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:614}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(10, 613)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.1923}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0734}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2855}

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0050202{col 30}{space 2} .0193724{col 41}{space 1}    0.26{col 50}{space 3}0.796{col 58}{space 4}-.0330241{col 71}{space 3} .0430645
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0042851{col 30}{space 2} .0661948{col 41}{space 1}   -0.06{col 50}{space 3}0.948{col 58}{space 4}-.1342813{col 71}{space 3}  .125711
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .9064998{col 30}{space 2}  .044583{col 41}{space 1}   20.33{col 50}{space 3}0.000{col 58}{space 4}  .818946{col 71}{space 3} .9940537
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.1402819{col 30}{space 2} .0578014{col 41}{space 1}   -2.43{col 50}{space 3}0.016{col 58}{space 4}-.2537947{col 71}{space 3}-.0267692
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0033801{col 30}{space 2} .0159706{col 41}{space 1}   -0.21{col 50}{space 3}0.832{col 58}{space 4}-.0347439{col 71}{space 3} .0279837
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0244428{col 30}{space 2} .0407454{col 41}{space 1}    0.60{col 50}{space 3}0.549{col 58}{space 4}-.0555747{col 71}{space 3} .1044602
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0112728{col 30}{space 2} .0220527{col 41}{space 1}    0.51{col 50}{space 3}0.609{col 58}{space 4}-.0320352{col 71}{space 3} .0545809
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0078029{col 30}{space 2} .0027549{col 41}{space 1}   -2.83{col 50}{space 3}0.005{col 58}{space 4} -.013213{col 71}{space 3}-.0023928
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0131109{col 30}{space 2} .0136339{col 41}{space 1}    0.96{col 50}{space 3}0.337{col 58}{space 4}-.0136639{col 71}{space 3} .0398857
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0512735{col 30}{space 2} .0518517{col 41}{space 1}   -0.99{col 50}{space 3}0.323{col 58}{space 4} -.153102{col 71}{space 3} .0505549
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0654774{col 30}{space 2} .0345274{col 41}{space 1}   -1.90{col 50}{space 3}0.058{col 58}{space 4}-.1332836{col 71}{space 3} .0023289
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1901791{col 30}{space 2} .0543622{col 41}{space 1}    3.50{col 50}{space 3}0.001{col 58}{space 4} .0834204{col 71}{space 3} .2969377
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,684
                                                {txt}{help j_robustsingular:F(10, 607) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0325
                                                {txt}Root MSE          =    {res} .23926

{txt}{ralign 82:(Std. err. adjusted for {res:608} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0242902{col 30}{space 2} .0133933{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4} -.050593{col 71}{space 3} .0020126
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0149049{col 30}{space 2} .0259256{col 41}{space 1}    0.57{col 50}{space 3}0.566{col 58}{space 4}  -.03601{col 71}{space 3} .0658197
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0730242{col 30}{space 2} .0167005{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4} -.105822{col 71}{space 3}-.0402265
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0246447{col 30}{space 2} .0218188{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.0674942{col 71}{space 3} .0182049
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0107111{col 30}{space 2}  .005233{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.0209881{col 71}{space 3}-.0004341
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0073546{col 30}{space 2} .0145829{col 41}{space 1}    0.50{col 50}{space 3}0.614{col 58}{space 4}-.0212844{col 71}{space 3} .0359937
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0174884{col 30}{space 2} .0105037{col 41}{space 1}    1.66{col 50}{space 3}0.096{col 58}{space 4}-.0031396{col 71}{space 3} .0381164
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0015556{col 30}{space 2}  .001049{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.0005046{col 71}{space 3} .0036158
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0493569{col 30}{space 2} .0082986{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .0330595{col 71}{space 3} .0656543
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0115187{col 30}{space 2} .0500427{col 41}{space 1}    0.23{col 50}{space 3}0.818{col 58}{space 4}-.0867591{col 71}{space 3} .1097965
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0341243{col 30}{space 2} .0221985{col 41}{space 1}   -1.54{col 50}{space 3}0.125{col 58}{space 4}-.0777195{col 71}{space 3}  .009471
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .000665{col 30}{space 2} .0240206{col 41}{space 1}    0.03{col 50}{space 3}0.978{col 58}{space 4}-.0465085{col 71}{space 3} .0478385
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,684}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:608}
{txt}{col 53}{lalign 17:F({res:10}, {res:607})}{col 70} = {res}{ralign 6:5.41}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2122}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0926}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2314}

{txt}{ralign 82:(Std. err. adjusted for {res:608} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0074142{col 30}{space 2} .0177503{col 41}{space 1}    0.42{col 50}{space 3}0.676{col 58}{space 4}-.0274452{col 71}{space 3} .0422736
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} -.003514{col 30}{space 2} .0617981{col 41}{space 1}   -0.06{col 50}{space 3}0.955{col 58}{space 4}-.1248781{col 71}{space 3} .1178502
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.1093004{col 30}{space 2} .0537458{col 41}{space 1}   -2.03{col 50}{space 3}0.042{col 58}{space 4}-.2148507{col 71}{space 3}-.0037501
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0084115{col 30}{space 2} .0138565{col 41}{space 1}   -0.61{col 50}{space 3}0.544{col 58}{space 4} -.035624{col 71}{space 3} .0188011
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0033463{col 30}{space 2} .0384261{col 41}{space 1}    0.09{col 50}{space 3}0.931{col 58}{space 4}-.0721179{col 71}{space 3} .0788105
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0127287{col 30}{space 2} .0226282{col 41}{space 1}    0.56{col 50}{space 3}0.574{col 58}{space 4}-.0317103{col 71}{space 3} .0571677
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0068737{col 30}{space 2} .0024656{col 41}{space 1}   -2.79{col 50}{space 3}0.005{col 58}{space 4}-.0117157{col 71}{space 3}-.0020316
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}  .014282{col 30}{space 2} .0120993{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0094797{col 71}{space 3} .0380437
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0089722{col 30}{space 2} .0498881{col 41}{space 1}   -0.18{col 50}{space 3}0.857{col 58}{space 4}-.1069465{col 71}{space 3} .0890021
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0277766{col 30}{space 2} .0277416{col 41}{space 1}   -1.00{col 50}{space 3}0.317{col 58}{space 4}-.0822578{col 71}{space 3} .0267047
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1392397{col 30}{space 2} .0496237{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0417848{col 71}{space 3} .2366947
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
. 
.         *Continue table
.         tex Electoral victory & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         tex Electoral victory (FE) & `b1f_donate_15any' & `b1f_b5' & `b1f_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_vf_donate_15any' & `p_vf_b5' & `p_vf_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lcif_donate_15any',`ucif_donate_15any'] & [`lcif_b5',`uci_b5'] & [`lcif_b2b',`ucif_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on donating in the next election. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, and non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG5.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(1,904 real changes made, 1,904 to missing)

{com}. 
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG5.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG5.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG5.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations for close elections (donor-level){c )-}\label{c -(}tab:donations_d_ols_cl{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.         
.                 quietly: rdrobust `var' margin_victory, p(1) vce(cluster muni_code) 
{txt}  3{com}.                 
.                 *Local's for the table
.                 local bw : di %5.2f `e(h_l)'
{txt}  4{com}.                 
.                 *No Family
.                 *Regressions
.                 quietly: regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim if margin_victory<=`bw',vce(cluster muni_code)
{txt}  5{com}.                 quietly sum `var' if e(sample)
{txt}  6{com}.                         local mean_`var' : di %5.3f r(mean)
{txt}  7{com}.                         local sd_`var' : di %5.3f r(sd)                 
{txt}  8{com}.                 
.                 regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim if margin_victory<=`bw',vce(cluster muni_code)
{txt}  9{com}. 
.                 local N_`var' : di %5.0f e(N)
{txt} 10{com}. 
.                 matrix b = e(b)
{txt} 11{com}.                 matrix v = e(V)
{txt} 12{com}.                 matrix res=r(table)
{txt} 13{com}.                 
.                 local b1_`var' : di %5.3f b[1,1]
{txt} 14{com}.                 local se1_`var' : di %5.3f sqrt(v[1,1])
{txt} 15{com}.                 local p_v_`var' :di %5.3f res[4,1]
{txt} 16{com}.                 local uci_`var': di %5.3f res[6,1]
{txt} 17{com}.                 local lci_`var': di %5.3f res[5,1]
{txt} 18{com}.                 
.                 areg `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 19{com}. 
.                 local Nf_`var' : di %5.0f e(N)
{txt} 20{com}. 
.                 matrix bf = e(b)
{txt} 21{com}.                 matrix vf = e(V)
{txt} 22{com}.                 matrix resf=r(table)
{txt} 23{com}.                 
.                 local b1f_`var' : di %5.3f bf[1,1]
{txt} 24{com}.                 local se1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 25{com}.                 local p_vf_`var' :di %5.3f resf[4,1]
{txt} 26{com}.                 local ucif_`var': di %5.3f resf[6,1]
{txt} 27{com}.                 local lcif_`var': di %5.3f resf[5,1]
{txt} 28{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     3,426
                                                {txt}F(11, 501)        =  {res}     4.19
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0211
                                                {txt}Root MSE          =    {res} .29281

{txt}{ralign 82:(Std. err. adjusted for {res:502} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0380924{col 30}{space 2} .0126646{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.0629748{col 71}{space 3}-.0132101
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0153361{col 30}{space 2} .0180106{col 41}{space 1}   -0.85{col 50}{space 3}0.395{col 58}{space 4}-.0507217{col 71}{space 3} .0200495
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .3799198{col 30}{space 2}  .368867{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.3447969{col 71}{space 3} 1.104637
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0643794{col 30}{space 2} .0259808{col 41}{space 1}   -2.48{col 50}{space 3}0.014{col 58}{space 4}-.1154242{col 71}{space 3}-.0133347
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0021937{col 30}{space 2} .0057288{col 41}{space 1}   -0.38{col 50}{space 3}0.702{col 58}{space 4}-.0134491{col 71}{space 3} .0090617
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0124601{col 30}{space 2} .0172128{col 41}{space 1}   -0.72{col 50}{space 3}0.469{col 58}{space 4}-.0462784{col 71}{space 3} .0213581
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0017877{col 30}{space 2} .0143613{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4} -.026428{col 71}{space 3} .0300035
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0005389{col 30}{space 2} .0019845{col 41}{space 1}    0.27{col 50}{space 3}0.786{col 58}{space 4}  -.00336{col 71}{space 3} .0044378
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0414022{col 30}{space 2} .0160326{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .0099028{col 71}{space 3} .0729017
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0009219{col 30}{space 2} .0708826{col 41}{space 1}    0.01{col 50}{space 3}0.990{col 58}{space 4}-.1383418{col 71}{space 3} .1401856
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0363349{col 30}{space 2} .0304728{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.0962052{col 71}{space 3} .0235353
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0976772{col 30}{space 2} .0363318{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0262957{col 71}{space 3} .1690587
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:3,426}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:502}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(10, 501)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2420}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1088}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2789}

{txt}{ralign 82:(Std. err. adjusted for {res:502} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0189639{col 30}{space 2} .0173749{col 41}{space 1}   -1.09{col 50}{space 3}0.276{col 58}{space 4}-.0531006{col 71}{space 3} .0151728
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0898664{col 30}{space 2} .0360964{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.1607853{col 71}{space 3}-.0189475
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .9479841{col 30}{space 2} .0529922{col 41}{space 1}   17.89{col 50}{space 3}0.000{col 58}{space 4} .8438698{col 71}{space 3} 1.052098
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0833888{col 30}{space 2} .0703178{col 41}{space 1}   -1.19{col 50}{space 3}0.236{col 58}{space 4}-.2215429{col 71}{space 3} .0547652
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0139742{col 30}{space 2} .0129331{col 41}{space 1}    1.08{col 50}{space 3}0.280{col 58}{space 4}-.0114357{col 71}{space 3}  .039384
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} -.032872{col 30}{space 2} .0336024{col 41}{space 1}   -0.98{col 50}{space 3}0.328{col 58}{space 4}-.0988909{col 71}{space 3}  .033147
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0005648{col 30}{space 2} .0232107{col 41}{space 1}   -0.02{col 50}{space 3}0.981{col 58}{space 4}-.0461671{col 71}{space 3} .0450376
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0084024{col 30}{space 2} .0034436{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4} -.015168{col 71}{space 3}-.0016368
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}  .012235{col 30}{space 2} .0224313{col 41}{space 1}    0.55{col 50}{space 3}0.586{col 58}{space 4}-.0318361{col 71}{space 3}  .056306
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0644887{col 30}{space 2} .0806183{col 41}{space 1}   -0.80{col 50}{space 3}0.424{col 58}{space 4}-.2228804{col 71}{space 3} .0939029
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.057631{col 30}{space 2} .0435514{col 41}{space 1}   -1.32{col 50}{space 3}0.186{col 58}{space 4} -.143197{col 71}{space 3} .0279349
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .2038864{col 30}{space 2} .0641877{col 41}{space 1}    3.18{col 50}{space 3}0.002{col 58}{space 4} .0777761{col 71}{space 3} .3299967
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     3,033
                                                {txt}{help j_robustsingular:F(10, 475) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0297
                                                {txt}Root MSE          =    {res} .24438

{txt}{ralign 82:(Std. err. adjusted for {res:476} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.028104{col 30}{space 2} .0119462{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.0515779{col 71}{space 3}  -.00463
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0124707{col 30}{space 2}  .018568{col 41}{space 1}   -0.67{col 50}{space 3}0.502{col 58}{space 4}-.0489563{col 71}{space 3} .0240149
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0969621{col 30}{space 2} .0138737{col 41}{space 1}   -6.99{col 50}{space 3}0.000{col 58}{space 4}-.1242236{col 71}{space 3}-.0697007
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0604978{col 30}{space 2} .0252712{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4} -.110155{col 71}{space 3}-.0108406
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0050114{col 30}{space 2} .0051081{col 41}{space 1}   -0.98{col 50}{space 3}0.327{col 58}{space 4}-.0150486{col 71}{space 3} .0050259
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0149775{col 30}{space 2}  .016394{col 41}{space 1}   -0.91{col 50}{space 3}0.361{col 58}{space 4}-.0471913{col 71}{space 3} .0172362
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0136135{col 30}{space 2} .0130336{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0119972{col 71}{space 3} .0392242
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}     .002{col 30}{space 2} .0017246{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.0013888{col 71}{space 3} .0053888
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0493851{col 30}{space 2} .0153288{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0192644{col 71}{space 3} .0795058
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0398932{col 30}{space 2} .0793464{col 41}{space 1}    0.50{col 50}{space 3}0.615{col 58}{space 4}-.1160202{col 71}{space 3} .1958066
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0306253{col 30}{space 2} .0295564{col 41}{space 1}   -1.04{col 50}{space 3}0.301{col 58}{space 4}-.0887028{col 71}{space 3} .0274521
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0311434{col 30}{space 2} .0322655{col 41}{space 1}    0.97{col 50}{space 3}0.335{col 58}{space 4}-.0322574{col 71}{space 3} .0945442
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:3,033}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:476}
{txt}{col 53}{lalign 17:F({res:10}, {res:475})}{col 70} = {res}{ralign 6:3.81}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0001}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2742}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1360}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2302}

{txt}{ralign 82:(Std. err. adjusted for {res:476} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0193504{col 30}{space 2} .0170115{col 41}{space 1}   -1.14{col 50}{space 3}0.256{col 58}{space 4}-.0527776{col 71}{space 3} .0140767
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0713594{col 30}{space 2} .0374938{col 41}{space 1}   -1.90{col 50}{space 3}0.058{col 58}{space 4}-.1450337{col 71}{space 3} .0023149
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0674076{col 30}{space 2} .0689536{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-.2028993{col 71}{space 3} .0680842
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0073723{col 30}{space 2} .0117196{col 41}{space 1}    0.63{col 50}{space 3}0.530{col 58}{space 4}-.0156564{col 71}{space 3}  .030401
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0290129{col 30}{space 2} .0339806{col 41}{space 1}   -0.85{col 50}{space 3}0.394{col 58}{space 4}-.0957838{col 71}{space 3}  .037758
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0072872{col 30}{space 2} .0218106{col 41}{space 1}    0.33{col 50}{space 3}0.738{col 58}{space 4}  -.03557{col 71}{space 3} .0501444
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0056274{col 30}{space 2} .0035347{col 41}{space 1}   -1.59{col 50}{space 3}0.112{col 58}{space 4}-.0125729{col 71}{space 3} .0013182
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0255857{col 30}{space 2} .0218822{col 41}{space 1}    1.17{col 50}{space 3}0.243{col 58}{space 4}-.0174121{col 71}{space 3} .0685836
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0170893{col 30}{space 2} .0817364{col 41}{space 1}   -0.21{col 50}{space 3}0.834{col 58}{space 4}-.1776989{col 71}{space 3} .1435203
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0012193{col 30}{space 2} .0339554{col 41}{space 1}   -0.04{col 50}{space 3}0.971{col 58}{space 4}-.0679406{col 71}{space 3}  .065502
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .119656{col 30}{space 2} .0548223{col 41}{space 1}    2.18{col 50}{space 3}0.030{col 58}{space 4} .0119318{col 71}{space 3} .2273802
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
. 
.         *Continue table
.         tex Electoral victory & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         tex Electoral victory (FE) & `b1f_donate_15any' & `b1f_b5' & `b1f_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_vf_donate_15any' & `p_vf_b5' & `p_vf_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lcif_donate_15any',`ucif_donate_15any'] & [`lcif_b5',`uci_b5'] & [`lcif_b2b',`ucif_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}\footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on donating in the next election. Samples correspond to observations within RD MSE optimal bandwidth. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, and rank of donation among all donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG6.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(2,365 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(6,166 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(2,365 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(6,166 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(6,166 missing values generated)

{com}. gen fgot_above_ext = got_above_ext if family==1
{txt}(6,166 missing values generated)

{com}. 
. 
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(370 real changes made, 370 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG6.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG6.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG6.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on benefits to donors (donor-level){c )-}\label{c -(}tab:table_benefits_ols{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c{c )-} \hline
{res}{txt}
{com}.         tex Outcome:& \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Total contracts{c )-}&\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Receive contract{c )-}&Receive contract& Runs in 2015\\
{res}{txt}
{com}.         tex &  \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} &\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} & (outside)& \\
{res}{txt}
{com}.         tex & Non-Family &Family & Non-Family &Family  & Family &Family \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4)& (5) & (6)\\ \hline
{res}{txt}
{com}.         tex & & & & & &\\
{res}{txt}
{com}.         
.         *preserve
.         *drop contract
.         *rename got_any contract
.         
.         *Model 1
.         foreach x in  total_cont_num_d contract{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum nf`x' if e(sample)
{txt}  4{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 regress nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim, vce(cluster muni_code)
{txt}  7{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
. 
.                 areg nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}.         
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local nfb1f_`x' : di %5.3f bf[1,1]
{txt} 22{com}.                 local nfse1f_`x' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local nfp_vf_`x' :di %5.3f resf[4,1]
{txt} 24{com}.                 local nfucif_`x': di %5.3f resf[6,1]
{txt} 25{com}.                 local nflcif_`x': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     4,863
                                                {txt}F(11, 613)        =  {res}     5.77
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0073
                                                {txt}Root MSE          =    {res} 4.0954

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}nftotal_cont_n~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}  .640155{col 30}{space 2}  .122466{col 41}{space 1}    5.23{col 50}{space 3}0.000{col 58}{space 4} .3996512{col 71}{space 3} .8806587
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0531247{col 30}{space 2} .2162661{col 41}{space 1}   -0.25{col 50}{space 3}0.806{col 58}{space 4} -.477837{col 71}{space 3} .3715875
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.6964558{col 30}{space 2} .2574564{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4}-1.202059{col 71}{space 3}-.1908522
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.3305025{col 30}{space 2} .3154426{col 41}{space 1}   -1.05{col 50}{space 3}0.295{col 58}{space 4}-.9499817{col 71}{space 3} .2889767
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0470607{col 30}{space 2} .0783321{col 41}{space 1}    0.60{col 50}{space 3}0.548{col 58}{space 4}-.1067711{col 71}{space 3} .2008925
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}  .137481{col 30}{space 2} .1980482{col 41}{space 1}    0.69{col 50}{space 3}0.488{col 58}{space 4}-.2514543{col 71}{space 3} .5264163
{txt}{space 10}center {c |}{col 18}{res}{space 2} .1165173{col 30}{space 2}  .157277{col 41}{space 1}    0.74{col 50}{space 3}0.459{col 58}{space 4}-.1923497{col 71}{space 3} .4253844
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0009193{col 30}{space 2} .0212678{col 41}{space 1}    0.04{col 50}{space 3}0.966{col 58}{space 4}-.0408473{col 71}{space 3}  .042686
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.0430915{col 30}{space 2} .1066679{col 41}{space 1}   -0.40{col 50}{space 3}0.686{col 58}{space 4}-.2525704{col 71}{space 3} .1663874
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.6854019{col 30}{space 2} .1008046{col 41}{space 1}   -6.80{col 50}{space 3}0.000{col 58}{space 4}-.8833663{col 71}{space 3}-.4874376
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.1479038{col 30}{space 2} .1936419{col 41}{space 1}   -0.76{col 50}{space 3}0.445{col 58}{space 4}-.5281857{col 71}{space 3} .2323781
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3856429{col 30}{space 2} .2422779{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.0901525{col 71}{space 3} .8614383
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,863}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:614}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(10, 613)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.1650}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0421}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:4.0179}

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}nftotal_cont_n~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .5535655{col 30}{space 2} .1533597{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .2523913{col 71}{space 3} .8547397
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.4878327{col 30}{space 2} .2856329{col 41}{space 1}   -1.71{col 50}{space 3}0.088{col 58}{space 4} -1.04877{col 71}{space 3}  .073105
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.6855362{col 30}{space 2} .4567444{col 41}{space 1}   -1.50{col 50}{space 3}0.134{col 58}{space 4} -1.58251{col 71}{space 3} .2114373
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.8493985{col 30}{space 2} .6323281{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-2.091191{col 71}{space 3} .3923937
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.1408441{col 30}{space 2} .1645562{col 41}{space 1}   -0.86{col 50}{space 3}0.392{col 58}{space 4}-.4640064{col 71}{space 3} .1823182
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .3742729{col 30}{space 2} .2620663{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.1403839{col 71}{space 3} .8889296
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0164309{col 30}{space 2} .1768905{col 41}{space 1}    0.09{col 50}{space 3}0.926{col 58}{space 4} -.330954{col 71}{space 3} .3638158
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0005109{col 30}{space 2} .0278163{col 41}{space 1}    0.02{col 50}{space 3}0.985{col 58}{space 4}-.0541159{col 71}{space 3} .0551376
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}  .115751{col 30}{space 2} .1074325{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.0952294{col 71}{space 3} .3267313
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-2.070367{col 30}{space 2}  1.63783{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-5.286806{col 71}{space 3} 1.146071
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0362716{col 30}{space 2} .2815618{col 41}{space 1}    0.13{col 50}{space 3}0.898{col 58}{space 4}-.5166711{col 71}{space 3} .5892144
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .658374{col 30}{space 2} .5228604{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.3684409{col 71}{space 3} 1.685189
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,863
                                                {txt}F(11, 613)        =  {res}     6.46
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0233
                                                {txt}Root MSE          =    {res} .30733

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}      nfcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0772701{col 30}{space 2}  .012446{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4} .0528281{col 71}{space 3} .1017122
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0224972{col 30}{space 2} .0313417{col 41}{space 1}    0.72{col 50}{space 3}0.473{col 58}{space 4}-.0390529{col 71}{space 3} .0840474
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1198211{col 30}{space 2} .0274199{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4}-.1736694{col 71}{space 3}-.0659729
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0355397{col 30}{space 2} .0285252{col 41}{space 1}   -1.25{col 50}{space 3}0.213{col 58}{space 4}-.0915587{col 71}{space 3} .0204792
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0214541{col 30}{space 2} .0103589{col 41}{space 1}    2.07{col 50}{space 3}0.039{col 58}{space 4} .0011108{col 71}{space 3} .0417974
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} -.024251{col 30}{space 2} .0203635{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.0642417{col 71}{space 3} .0157397
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0154022{col 30}{space 2} .0151004{col 41}{space 1}    1.02{col 50}{space 3}0.308{col 58}{space 4}-.0142527{col 71}{space 3}  .045057
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0008928{col 30}{space 2} .0017491{col 41}{space 1}   -0.51{col 50}{space 3}0.610{col 58}{space 4}-.0043278{col 71}{space 3} .0025421
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.0186689{col 30}{space 2} .0126262{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.0434648{col 71}{space 3} .0061269
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0749964{col 30}{space 2} .0340617{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.1418882{col 71}{space 3}-.0081046
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0040227{col 30}{space 2} .0205126{col 41}{space 1}   -0.20{col 50}{space 3}0.845{col 58}{space 4}-.0443062{col 71}{space 3} .0362609
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0976644{col 30}{space 2}  .023382{col 41}{space 1}    4.18{col 50}{space 3}0.000{col 58}{space 4}  .051746{col 71}{space 3} .1435829
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,863}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:614}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(10, 613)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2103}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0940}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2956}

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}      nfcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}  .074028{col 30}{space 2} .0160307{col 41}{space 1}    4.62{col 50}{space 3}0.000{col 58}{space 4} .0425462{col 71}{space 3} .1055098
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.1049916{col 30}{space 2} .0371839{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.1780148{col 71}{space 3}-.0319683
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1368471{col 30}{space 2} .0438948{col 41}{space 1}   -3.12{col 50}{space 3}0.002{col 58}{space 4}-.2230496{col 71}{space 3}-.0506446
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.1136264{col 30}{space 2} .0551579{col 41}{space 1}   -2.06{col 50}{space 3}0.040{col 58}{space 4}-.2219478{col 71}{space 3} -.005305
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0052862{col 30}{space 2} .0196634{col 41}{space 1}   -0.27{col 50}{space 3}0.788{col 58}{space 4} -.043902{col 71}{space 3} .0333296
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0051228{col 30}{space 2} .0291694{col 41}{space 1}    0.18{col 50}{space 3}0.861{col 58}{space 4}-.0521614{col 71}{space 3} .0624069
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0253861{col 30}{space 2}  .020347{col 41}{space 1}   -1.25{col 50}{space 3}0.213{col 58}{space 4}-.0653444{col 71}{space 3} .0145723
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}  .000269{col 30}{space 2} .0025042{col 41}{space 1}    0.11{col 50}{space 3}0.914{col 58}{space 4}-.0046488{col 71}{space 3} .0051869
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.0070754{col 30}{space 2} .0169305{col 41}{space 1}   -0.42{col 50}{space 3}0.676{col 58}{space 4}-.0403242{col 71}{space 3} .0261734
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0754556{col 30}{space 2} .0439916{col 41}{space 1}   -1.72{col 50}{space 3}0.087{col 58}{space 4}-.1618482{col 71}{space 3} .0109369
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0163679{col 30}{space 2} .0325851{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0476241{col 71}{space 3} .0803598
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1723662{col 30}{space 2} .0500179{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4}  .074139{col 71}{space 3} .2705934
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(2,365 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(6,166 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(2,365 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(6,166 missing values generated)

{com}. gen nfruns_any = runs_any if family==0
{txt}(2,365 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(6,166 missing values generated)

{com}. gen nfgot_above_ext = got_above_ext if family==0
{txt}(2,370 missing values generated)

{com}. gen fgot_above_ext = got_above_ext if family==1
{txt}(6,166 missing values generated)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(1,904 real changes made, 1,904 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(1,904 missing values generated)

{com}. 
.         
.         foreach x in  total_cont_num_d contract got_above_ext runs_any{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 regress f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.                 areg f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}.                 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local fb1f_`x' : di %5.3f bf[1,1]
{txt} 22{com}.                 local fse1f_`x' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local fp_vf_`x' :di %5.3f resf[4,1]
{txt} 24{com}.                 local fucif_`x': di %5.3f resf[6,1]
{txt} 25{com}.                 local flcif_`x': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,758
                                                {txt}F(11, 611)        =  {res}     0.59
                                                {txt}Prob > F          = {res}    0.8341
                                                {txt}R-squared         = {res}    0.0039
                                                {txt}Root MSE          =    {res} .11438

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}ftotal_cont_nu~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0081865{col 30}{space 2} .0063597{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4} -.020676{col 71}{space 3}  .004303
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0085747{col 30}{space 2} .0040641{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4} -.016556{col 71}{space 3}-.0005933
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0030216{col 30}{space 2} .0055637{col 41}{space 1}   -0.54{col 50}{space 3}0.587{col 58}{space 4}-.0139478{col 71}{space 3} .0079047
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0161712{col 30}{space 2} .0176286{col 41}{space 1}    0.92{col 50}{space 3}0.359{col 58}{space 4}-.0184489{col 71}{space 3} .0507912
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0018276{col 30}{space 2} .0027007{col 41}{space 1}    0.68{col 50}{space 3}0.499{col 58}{space 4}-.0034761{col 71}{space 3} .0071314
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0002954{col 30}{space 2} .0067428{col 41}{space 1}    0.04{col 50}{space 3}0.965{col 58}{space 4}-.0129465{col 71}{space 3} .0135373
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0062197{col 30}{space 2} .0040321{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0016988{col 71}{space 3} .0141382
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} -.000733{col 30}{space 2}  .001356{col 41}{space 1}   -0.54{col 50}{space 3}0.589{col 58}{space 4} -.003396{col 71}{space 3}   .00193
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0020737{col 30}{space 2} .0047793{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0073123{col 71}{space 3} .0114596
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} -.006915{col 30}{space 2} .0044204{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4} -.015596{col 71}{space 3} .0017659
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0043119{col 30}{space 2} .0109469{col 41}{space 1}    0.39{col 50}{space 3}0.694{col 58}{space 4}-.0171862{col 71}{space 3}   .02581
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -.000405{col 30}{space 2} .0081212{col 41}{space 1}   -0.05{col 50}{space 3}0.960{col 58}{space 4}-.0163537{col 71}{space 3} .0155438
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 52}{lalign 17:Number of obs}{col 69} = {res}{ralign 7:1,758}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 52}{lalign 17:No. of categories}{col 69} = {res}{ralign 7:612}
{txt}{col 52}{lalign 17:F({res:10}, {res:611})}{col 69} = {res}{ralign 7:0.32}
{txt}{col 52}{lalign 17:Prob > F}{col 69} = {res}{ralign 7:0.9753}
{txt}{col 52}{lalign 17:R-squared}{col 69} = {res}{ralign 7:0.3209}
{txt}{col 52}{lalign 17:Adj R-squared}{col 69} = {res}{ralign 7:-0.0503}
{txt}{col 52}{lalign 17:Root MSE}{col 69} = {res}{ralign 7:0.1171}

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}ftotal_cont_nu~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0105016{col 30}{space 2} .0119187{col 41}{space 1}   -0.88{col 50}{space 3}0.379{col 58}{space 4}-.0339082{col 71}{space 3}  .012905
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0038833{col 30}{space 2} .0067691{col 41}{space 1}   -0.57{col 50}{space 3}0.566{col 58}{space 4}-.0171768{col 71}{space 3} .0094102
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0316305{col 30}{space 2} .0233333{col 41}{space 1}   -1.36{col 50}{space 3}0.176{col 58}{space 4}-.0774537{col 71}{space 3} .0141928
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0015115{col 30}{space 2} .0027124{col 41}{space 1}   -0.56{col 50}{space 3}0.578{col 58}{space 4}-.0068382{col 71}{space 3} .0038152
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0075991{col 30}{space 2} .0178672{col 41}{space 1}    0.43{col 50}{space 3}0.671{col 58}{space 4}-.0274895{col 71}{space 3} .0426878
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0184779{col 30}{space 2} .0216866{col 41}{space 1}    0.85{col 50}{space 3}0.395{col 58}{space 4}-.0241115{col 71}{space 3} .0610672
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0018597{col 30}{space 2} .0023207{col 41}{space 1}   -0.80{col 50}{space 3}0.423{col 58}{space 4}-.0064171{col 71}{space 3} .0026977
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0058692{col 30}{space 2} .0136107{col 41}{space 1}   -0.43{col 50}{space 3}0.666{col 58}{space 4}-.0325988{col 71}{space 3} .0208603
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.1298791{col 30}{space 2} .1126723{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.3511511{col 71}{space 3}  .091393
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0065228{col 30}{space 2} .0162708{col 41}{space 1}    0.40{col 50}{space 3}0.689{col 58}{space 4}-.0254308{col 71}{space 3} .0384763
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0180737{col 30}{space 2} .0287208{col 41}{space 1}    0.63{col 50}{space 3}0.529{col 58}{space 4}-.0383298{col 71}{space 3} .0744771
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,758
                                                {txt}F(11, 611)        =  {res}     0.65
                                                {txt}Prob > F          = {res}    0.7854
                                                {txt}R-squared         = {res}    0.0031
                                                {txt}Root MSE          =    {res} .06309

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0027464{col 30}{space 2} .0032927{col 41}{space 1}   -0.83{col 50}{space 3}0.405{col 58}{space 4}-.0092128{col 71}{space 3} .0037199
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0055254{col 30}{space 2} .0025503{col 41}{space 1}   -2.17{col 50}{space 3}0.031{col 58}{space 4}-.0105338{col 71}{space 3}-.0005171
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0021964{col 30}{space 2} .0030332{col 41}{space 1}   -0.72{col 50}{space 3}0.469{col 58}{space 4}-.0081532{col 71}{space 3} .0037605
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0050924{col 30}{space 2} .0076665{col 41}{space 1}    0.66{col 50}{space 3}0.507{col 58}{space 4}-.0099634{col 71}{space 3} .0201482
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0020844{col 30}{space 2} .0025383{col 41}{space 1}    0.82{col 50}{space 3}0.412{col 58}{space 4}-.0029005{col 71}{space 3} .0070694
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0015815{col 30}{space 2} .0036537{col 41}{space 1}   -0.43{col 50}{space 3}0.665{col 58}{space 4}-.0087568{col 71}{space 3} .0055939
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0030366{col 30}{space 2} .0024704{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.0018149{col 71}{space 3} .0078881
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0000514{col 30}{space 2} .0007408{col 41}{space 1}   -0.07{col 50}{space 3}0.945{col 58}{space 4}-.0015062{col 71}{space 3} .0014033
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0023816{col 30}{space 2} .0037248{col 41}{space 1}    0.64{col 50}{space 3}0.523{col 58}{space 4}-.0049334{col 71}{space 3} .0096966
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0038439{col 30}{space 2} .0027624{col 41}{space 1}   -1.39{col 50}{space 3}0.165{col 58}{space 4}-.0092688{col 71}{space 3}  .001581
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0011542{col 30}{space 2} .0066919{col 41}{space 1}    0.17{col 50}{space 3}0.863{col 58}{space 4}-.0119878{col 71}{space 3} .0142962
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0023434{col 30}{space 2} .0061933{col 41}{space 1}   -0.38{col 50}{space 3}0.705{col 58}{space 4}-.0145062{col 71}{space 3} .0098193
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,758}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:612}
{txt}{col 53}{lalign 17:F({res:10}, {res:611})}{col 70} = {res}{ralign 6:0.38}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.9567}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.3673}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0214}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.0623}

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0016922{col 30}{space 2} .0046232{col 41}{space 1}   -0.37{col 50}{space 3}0.714{col 58}{space 4}-.0107716{col 71}{space 3} .0073872
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0017525{col 30}{space 2} .0033896{col 41}{space 1}   -0.52{col 50}{space 3}0.605{col 58}{space 4}-.0084092{col 71}{space 3} .0049043
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0185925{col 30}{space 2} .0155032{col 41}{space 1}   -1.20{col 50}{space 3}0.231{col 58}{space 4}-.0490385{col 71}{space 3} .0118534
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} -.000587{col 30}{space 2} .0010416{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4}-.0026326{col 71}{space 3} .0014586
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0018553{col 30}{space 2} .0061757{col 41}{space 1}    0.30{col 50}{space 3}0.764{col 58}{space 4} -.010273{col 71}{space 3} .0139835
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0072466{col 30}{space 2} .0072439{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4}-.0069795{col 71}{space 3} .0214726
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0003911{col 30}{space 2} .0008861{col 41}{space 1}   -0.44{col 50}{space 3}0.659{col 58}{space 4}-.0021312{col 71}{space 3}  .001349
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0016334{col 30}{space 2} .0095088{col 41}{space 1}    0.17{col 50}{space 3}0.864{col 58}{space 4}-.0170404{col 71}{space 3} .0203073
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0696772{col 30}{space 2} .0576073{col 41}{space 1}   -1.21{col 50}{space 3}0.227{col 58}{space 4}-.1828095{col 71}{space 3} .0434551
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0023919{col 30}{space 2}  .011011{col 41}{space 1}   -0.22{col 50}{space 3}0.828{col 58}{space 4}-.0240159{col 71}{space 3} .0192321
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0020283{col 30}{space 2} .0186655{col 41}{space 1}    0.11{col 50}{space 3}0.914{col 58}{space 4}-.0346281{col 71}{space 3} .0386846
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,758
                                                {txt}F(11, 611)        =  {res}    10.26
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0098
                                                {txt}Root MSE          =    {res} .29277

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  fgot_above_ext{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0450162{col 30}{space 2} .0141316{col 41}{space 1}   -3.19{col 50}{space 3}0.002{col 58}{space 4}-.0727687{col 71}{space 3}-.0172638
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0345182{col 30}{space 2} .0226969{col 41}{space 1}   -1.52{col 50}{space 3}0.129{col 58}{space 4}-.0790916{col 71}{space 3} .0100553
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1062393{col 30}{space 2} .0244285{col 41}{space 1}   -4.35{col 50}{space 3}0.000{col 58}{space 4}-.1542133{col 71}{space 3}-.0582654
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0311066{col 30}{space 2} .0328508{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.0956208{col 71}{space 3} .0334076
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}  .005878{col 30}{space 2} .0101195{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0139951{col 71}{space 3} .0257512
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0081034{col 30}{space 2} .0193057{col 41}{space 1}    0.42{col 50}{space 3}0.675{col 58}{space 4}-.0298102{col 71}{space 3} .0460171
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0055997{col 30}{space 2} .0150011{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.0350597{col 71}{space 3} .0238602
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0032837{col 30}{space 2}  .003573{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0037333{col 71}{space 3} .0103006
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0125457{col 30}{space 2} .0104503{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.0079772{col 71}{space 3} .0330686
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0987913{col 30}{space 2} .0116258{col 41}{space 1}   -8.50{col 50}{space 3}0.000{col 58}{space 4}-.1216226{col 71}{space 3}-.0759599
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0062234{col 30}{space 2}  .018784{col 41}{space 1}    0.33{col 50}{space 3}0.741{col 58}{space 4}-.0306657{col 71}{space 3} .0431124
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0949755{col 30}{space 2}   .02777{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0404393{col 71}{space 3} .1495117
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,758}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:612}
{txt}{col 53}{lalign 17:F({res:10}, {res:611})}{col 70} = {res}{ralign 6:1.74}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0688}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.3908}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0578}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2847}

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  fgot_above_ext{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0457805{col 30}{space 2} .0245874{col 41}{space 1}   -1.86{col 50}{space 3}0.063{col 58}{space 4}-.0940665{col 71}{space 3} .0025056
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0578193{col 30}{space 2} .0485465{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.1531575{col 71}{space 3} .0375189
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} -.000295{col 30}{space 2} .0840482{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.1653534{col 71}{space 3} .1647633
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0221708{col 30}{space 2} .0242029{col 41}{space 1}   -0.92{col 50}{space 3}0.360{col 58}{space 4}-.0697018{col 71}{space 3} .0253601
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0997334{col 30}{space 2}   .05043{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0006962{col 71}{space 3} .1987706
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0433967{col 30}{space 2} .0375145{col 41}{space 1}    1.16{col 50}{space 3}0.248{col 58}{space 4}-.0302763{col 71}{space 3} .1170697
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0011412{col 30}{space 2} .0081448{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4}-.0171365{col 71}{space 3}  .014854
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} -.026712{col 30}{space 2} .0324143{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.0903688{col 71}{space 3} .0369449
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.1215829{col 30}{space 2}  .058364{col 41}{space 1}   -2.08{col 50}{space 3}0.038{col 58}{space 4}-.2362014{col 71}{space 3}-.0069645
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0025236{col 30}{space 2} .0386533{col 41}{space 1}   -0.07{col 50}{space 3}0.948{col 58}{space 4}-.0784331{col 71}{space 3} .0733859
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1229294{col 30}{space 2} .0849414{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0438832{col 71}{space 3} .2897419
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,758
                                                {txt}F(11, 611)        =  {res}     2.07
                                                {txt}Prob > F          = {res}    0.0209
                                                {txt}R-squared         = {res}    0.0056
                                                {txt}Root MSE          =    {res} .11847

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fruns_any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0035773{col 30}{space 2} .0057774{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.0077687{col 71}{space 3} .0149234
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0018223{col 30}{space 2} .0084927{col 41}{space 1}   -0.21{col 50}{space 3}0.830{col 58}{space 4}-.0185007{col 71}{space 3} .0148562
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0132047{col 30}{space 2} .0055736{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.0241504{col 71}{space 3} -.002259
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0238372{col 30}{space 2} .0141831{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0040164{col 71}{space 3} .0516907
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0033861{col 30}{space 2} .0050588{col 41}{space 1}   -0.67{col 50}{space 3}0.504{col 58}{space 4}-.0133207{col 71}{space 3} .0065486
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0022264{col 30}{space 2} .0099474{col 41}{space 1}    0.22{col 50}{space 3}0.823{col 58}{space 4}-.0173089{col 71}{space 3} .0217617
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0053869{col 30}{space 2} .0066226{col 41}{space 1}    0.81{col 50}{space 3}0.416{col 58}{space 4}-.0076189{col 71}{space 3} .0183927
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0019437{col 30}{space 2} .0013152{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.0045266{col 71}{space 3} .0006393
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0036663{col 30}{space 2} .0030848{col 41}{space 1}   -1.19{col 50}{space 3}0.235{col 58}{space 4}-.0097244{col 71}{space 3} .0023917
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0180327{col 30}{space 2}   .00525{col 41}{space 1}   -3.43{col 50}{space 3}0.001{col 58}{space 4} -.028343{col 71}{space 3}-.0077225
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0151584{col 30}{space 2} .0082684{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0010795{col 71}{space 3} .0313963
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0119492{col 30}{space 2} .0076838{col 41}{space 1}    1.56{col 50}{space 3}0.120{col 58}{space 4}-.0031407{col 71}{space 3} .0270391
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 52}{lalign 17:Number of obs}{col 69} = {res}{ralign 7:1,758}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 52}{lalign 17:No. of categories}{col 69} = {res}{ralign 7:612}
{txt}{col 52}{lalign 17:F({res:10}, {res:611})}{col 69} = {res}{ralign 7:0.79}
{txt}{col 52}{lalign 17:Prob > F}{col 69} = {res}{ralign 7:0.6349}
{txt}{col 52}{lalign 17:R-squared}{col 69} = {res}{ralign 7:0.3395}
{txt}{col 52}{lalign 17:Adj R-squared}{col 69} = {res}{ralign 7:-0.0215}
{txt}{col 52}{lalign 17:Root MSE}{col 69} = {res}{ralign 7:0.1197}

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fruns_any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0057808{col 30}{space 2} .0115379{col 41}{space 1}   -0.50{col 50}{space 3}0.617{col 58}{space 4}-.0284395{col 71}{space 3}  .016878
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0116084{col 30}{space 2} .0143219{col 41}{space 1}    0.81{col 50}{space 3}0.418{col 58}{space 4}-.0165177{col 71}{space 3} .0397345
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .0764218{col 30}{space 2} .0511171{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0239648{col 71}{space 3} .1768083
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0209268{col 30}{space 2}  .013954{col 41}{space 1}   -1.50{col 50}{space 3}0.134{col 58}{space 4}-.0483305{col 71}{space 3} .0064769
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0200665{col 30}{space 2} .0199968{col 41}{space 1}    1.00{col 50}{space 3}0.316{col 58}{space 4}-.0192042{col 71}{space 3} .0593373
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0119445{col 30}{space 2} .0145187{col 41}{space 1}   -0.82{col 50}{space 3}0.411{col 58}{space 4}-.0404572{col 71}{space 3} .0165682
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} -.006944{col 30}{space 2} .0032013{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4} -.013231{col 71}{space 3} -.000657
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0228469{col 30}{space 2}  .012571{col 41}{space 1}   -1.82{col 50}{space 3}0.070{col 58}{space 4}-.0475346{col 71}{space 3} .0018408
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0110169{col 30}{space 2} .0074586{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.0256646{col 71}{space 3} .0036308
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0410385{col 30}{space 2} .0174058{col 41}{space 1}    2.36{col 50}{space 3}0.019{col 58}{space 4} .0068559{col 71}{space 3}  .075221
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0615505{col 30}{space 2} .0275007{col 41}{space 1}    2.24{col 50}{space 3}0.026{col 58}{space 4} .0075431{col 71}{space 3} .1155578
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         
. 
.         *Continue table
.         tex Electoral victory & `nfb1_total_cont_num_d' &  `fb1_total_cont_num_d'& `nfb1_contract' & `fb1_contract' & `fb1_got_above_ext' & `fb1_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \  p-value & `nfp_v_total_cont_num_d' &  `fp_v_total_cont_num_d' & `nfp_v_contract' & `fp_v_contract' & `fp_v_got_above_ext' & `fp_v_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_total_cont_num_d',`nfuci_total_cont_num_d'] & [`flci_total_cont_num_d',`fuci_total_cont_num_d'] &  [`nflci_contract',`nfuci_contract'] & [`flci_contract',`fuci_contract'] & [`flci_got_above_ext',`fuci_got_above_ext'] & [`flci_runs_any',`fuci_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}. 
.         tex Electoral victory (FE) & `nfb1f_total_cont_num_d' &  `fb1f_total_cont_num_d'& `nfb1f_contract' & `fb1f_contract' & `fb1f_got_above_ext' & `fb1f_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \  p-value & `nfp_vf_total_cont_num_d' &  `fp_vf_total_cont_num_d' & `nfp_vf_contract' & `fp_vf_contract' & `fp_vf_got_above_ext' & `fp_vf_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflcif_total_cont_num_d',`nfucif_total_cont_num_d'] & [`flcif_total_cont_num_d',`fucif_total_cont_num_d'] &  [`nflcif_contract',`nfucif_contract'] & [`flcif_contract',`fucif_contract'] & [`flcif_got_above_ext',`fucif_got_above_ext'] & [`flcif_runs_any',`fucif_runs_any']\\
{res}{txt}
{com}.         tex & & & \\    
{res}{txt}
{com}.         
.         
.         tex Observations &`nfN_total_cont_num_d' &  `fN_total_cont_num_d' & `nfN_contract'& `fN_contract' & `fN_got_above_ext' & `fN_runs_any' \\
{res}{txt}
{com}.         tex Mean & `nfmean_total_cont_num_d' &`fmean_total_cont_num_d'  &  `nfmean_contract' & `fmean_contract' & `fmean_got_above_ext' & `fmean_runs_any' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on benefits received by the donor. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, and non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all family and non-family donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.     tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG7.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. keep if rank==1|rank==2
{txt}(1,534 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(227 real changes made, 227 to missing)

{com}. 
. gen nfdonate_15any = donate_15any if family==0
{txt}(1,906 missing values generated)

{com}. gen fdonate_15any = donate_15any if family==1
{txt}(5,091 missing values generated)

{com}. gen nfb5 = b5 if family==0
{txt}(2,097 missing values generated)

{com}. gen fb5 = b5 if family==1
{txt}(5,127 missing values generated)

{com}. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if margin_victory>0&margin_victory~=.
{txt}(4,013 real changes made)

{com}. replace treat=. if margin_victory==.
{txt}(370 real changes made, 370 to missing)

{com}. 
. gen treat_margin_victory=treat*margin_victory
{txt}(370 missing values generated)

{com}. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG7.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG7.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG7.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members global parametric linear RD){c )-}\label{c -(}tab:donation_fam_nofam_l_ols{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c {c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor  \\ 
{res}{txt}
{com}.         tex & (1) & (2)  \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}\\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.                 
.                 quietly: regress f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`var' if e(sample)
{txt}  4{com}.                         local fmean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`var' : di %5.3f r(sd)                
{txt}  6{com}.                 
.                 regress f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`var' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`var' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`var' : di %5.3f b[1,1]
{txt} 13{com}.                 local fse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local fp_v_`var' :di %5.3f res[4,1]
{txt} 15{com}.                 local fuci_`var': di %5.3f res[6,1]
{txt} 16{com}.                 local flci_`var': di %5.3f res[5,1]
{txt} 17{com}. 
. 
.                 areg f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}. 
. 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local fb1f_`var' : di %5.3f bf[1,1]
{txt} 22{com}.                 local fse1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local fp_vf_`var' :di %5.3f resf[4,1]
{txt} 24{com}.                 local fucif_`var': di %5.3f resf[6,1]
{txt} 25{com}.                 local flcif_`var': di %5.3f resf[5,1]
{txt} 26{com}.                 
.                 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                         quietly: regress nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt} 27{com}.                         quietly sum nf`var' if e(sample)
{txt} 28{com}.                         local nfmean_`var' : di %5.3f r(mean)
{txt} 29{com}.                         local nfsd_`var' : di %5.3f r(sd)               
{txt} 30{com}.                 
.                 regress nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim, vce(cluster muni_code)
{txt} 31{com}. 
.                 local nfN_`var' : di %5.0f e(N)
{txt} 32{com}.                 local nfR2_`var' : di %5.3f e(r2)
{txt} 33{com}. 
.                 matrix b = e(b)
{txt} 34{com}.                 matrix v = e(V)
{txt} 35{com}.                 matrix res=r(table)
{txt} 36{com}.                 
.                 local nfb1_`var' : di %5.3f b[1,1]
{txt} 37{com}.                 local nfse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 38{com}.                 local nfp_v_`var' :di %5.3f res[4,1]
{txt} 39{com}.                 local nfuci_`var': di %5.3f res[6,1]
{txt} 40{com}.                 local nflci_`var': di %5.3f res[5,1]
{txt} 41{com}.         
.         
.         areg nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d center rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 42{com}.         
.         matrix bf = e(b)
{txt} 43{com}.                 matrix vf = e(V)
{txt} 44{com}.                 matrix resf=r(table)
{txt} 45{com}.                 
.                 local nfb1f_`var' : di %5.3f bf[1,1]
{txt} 46{com}.                 local nfse1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 47{com}.                 local nfp_vf_`var' :di %5.3f resf[4,1]
{txt} 48{com}.                 local nfucif_`var': di %5.3f resf[6,1]
{txt} 49{com}.                 local nflcif_`var': di %5.3f resf[5,1]
{txt} 50{com}.         
.         
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,758
                                                {txt}F(11, 611)        =  {res}     6.13
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0684
                                                {txt}Root MSE          =    {res}   .277

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   fdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.1437275{col 30}{space 2} .0190214{col 41}{space 1}   -7.56{col 50}{space 3}0.000{col 58}{space 4}-.1810828{col 71}{space 3}-.1063722
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0073316{col 30}{space 2} .0356057{col 41}{space 1}    0.21{col 50}{space 3}0.837{col 58}{space 4}-.0625929{col 71}{space 3} .0772561
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1123074{col 30}{space 2} .0509655{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.2123963{col 71}{space 3}-.0122185
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0404292{col 30}{space 2}  .038333{col 41}{space 1}    1.05{col 50}{space 3}0.292{col 58}{space 4}-.0348511{col 71}{space 3} .1157096
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0051093{col 30}{space 2} .0119181{col 41}{space 1}    0.43{col 50}{space 3}0.668{col 58}{space 4}-.0182962{col 71}{space 3} .0285148
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0157461{col 30}{space 2} .0228212{col 41}{space 1}   -0.69{col 50}{space 3}0.490{col 58}{space 4}-.0605636{col 71}{space 3} .0290715
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0035342{col 30}{space 2} .0182969{col 41}{space 1}    0.19{col 50}{space 3}0.847{col 58}{space 4}-.0323983{col 71}{space 3} .0394667
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0020986{col 30}{space 2} .0048421{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0074106{col 71}{space 3} .0116078
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0379081{col 30}{space 2} .0148187{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4} .0088064{col 71}{space 3} .0670098
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0150488{col 30}{space 2} .0736032{col 41}{space 1}   -0.20{col 50}{space 3}0.838{col 58}{space 4}-.1595949{col 71}{space 3} .1294972
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0177676{col 30}{space 2} .0218476{col 41}{space 1}   -0.81{col 50}{space 3}0.416{col 58}{space 4}-.0606731{col 71}{space 3}  .025138
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0930218{col 30}{space 2} .0325536{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0290912{col 71}{space 3} .1569524
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,758}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:612}
{txt}{col 53}{lalign 17:F({res:10}, {res:611})}{col 70} = {res}{ralign 6:2.57}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0047}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.5076}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.2384}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2497}

{txt}{ralign 82:(Std. err. adjusted for {res:612} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   fdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.1452889{col 30}{space 2} .0315466{col 41}{space 1}   -4.61{col 50}{space 3}0.000{col 58}{space 4}-.2072418{col 71}{space 3} -.083336
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0039483{col 30}{space 2}  .079664{col 41}{space 1}    0.05{col 50}{space 3}0.960{col 58}{space 4}-.1525001{col 71}{space 3} .1603967
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .1422507{col 30}{space 2} .1086291{col 41}{space 1}    1.31{col 50}{space 3}0.191{col 58}{space 4}-.0710809{col 71}{space 3} .3555823
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0331412{col 30}{space 2} .0348176{col 41}{space 1}   -0.95{col 50}{space 3}0.342{col 58}{space 4}-.1015179{col 71}{space 3} .0352355
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0181076{col 30}{space 2} .0563999{col 41}{space 1}    0.32{col 50}{space 3}0.748{col 58}{space 4}-.0926536{col 71}{space 3} .1288688
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0133366{col 30}{space 2} .0447684{col 41}{space 1}   -0.30{col 50}{space 3}0.766{col 58}{space 4}-.1012551{col 71}{space 3} .0745819
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0069169{col 30}{space 2} .0098078{col 41}{space 1}   -0.71{col 50}{space 3}0.481{col 58}{space 4} -.026178{col 71}{space 3} .0123441
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}  .009091{col 30}{space 2} .0337384{col 41}{space 1}    0.27{col 50}{space 3}0.788{col 58}{space 4}-.0571663{col 71}{space 3} .0753483
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0701056{col 30}{space 2} .0985625{col 41}{space 1}    0.71{col 50}{space 3}0.477{col 58}{space 4}-.1234568{col 71}{space 3}  .263668
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0181195{col 30}{space 2} .0381228{col 41}{space 1}    0.48{col 50}{space 3}0.635{col 58}{space 4}-.0567481{col 71}{space 3} .0929872
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1582964{col 30}{space 2} .0798542{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0014744{col 71}{space 3} .3151184
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,863
                                                {txt}F(11, 613)        =  {res}     5.46
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0225
                                                {txt}Root MSE          =    {res} .29361

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  nfdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0300134{col 30}{space 2} .0152932{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.0600469{col 71}{space 3}   .00002
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0210913{col 30}{space 2}  .030859{col 41}{space 1}    0.68{col 50}{space 3}0.495{col 58}{space 4}-.0395109{col 71}{space 3} .0816936
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .4088621{col 30}{space 2} .3698552{col 41}{space 1}    1.11{col 50}{space 3}0.269{col 58}{space 4}-.3174748{col 71}{space 3} 1.135199
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0263866{col 30}{space 2} .0259482{col 41}{space 1}   -1.02{col 50}{space 3}0.310{col 58}{space 4}-.0773448{col 71}{space 3} .0245715
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0106556{col 30}{space 2} .0065596{col 41}{space 1}   -1.62{col 50}{space 3}0.105{col 58}{space 4}-.0235375{col 71}{space 3} .0022264
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0072159{col 30}{space 2} .0170939{col 41}{space 1}    0.42{col 50}{space 3}0.673{col 58}{space 4}-.0263538{col 71}{space 3} .0407856
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0109056{col 30}{space 2} .0126243{col 41}{space 1}    0.86{col 50}{space 3}0.388{col 58}{space 4}-.0138865{col 71}{space 3} .0356977
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0010363{col 30}{space 2}  .001242{col 41}{space 1}    0.83{col 50}{space 3}0.404{col 58}{space 4}-.0014029{col 71}{space 3} .0034755
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0477787{col 30}{space 2} .0086853{col 41}{space 1}    5.50{col 50}{space 3}0.000{col 58}{space 4} .0307222{col 71}{space 3} .0648352
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0234817{col 30}{space 2} .0500654{col 41}{space 1}   -0.47{col 50}{space 3}0.639{col 58}{space 4}-.1218022{col 71}{space 3} .0748388
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.049187{col 30}{space 2} .0237587{col 41}{space 1}   -2.07{col 50}{space 3}0.039{col 58}{space 4}-.0958453{col 71}{space 3}-.0025287
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .049654{col 30}{space 2} .0290823{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4} -.007459{col 71}{space 3}  .106767
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,863}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:614}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(10, 613)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.1923}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0734}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2855}

{txt}{ralign 82:(Std. err. adjusted for {res:614} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  nfdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0050139{col 30}{space 2} .0194062{col 41}{space 1}    0.26{col 50}{space 3}0.796{col 58}{space 4}-.0330969{col 71}{space 3} .0431246
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0041951{col 30}{space 2}  .066115{col 41}{space 1}   -0.06{col 50}{space 3}0.949{col 58}{space 4}-.1340344{col 71}{space 3} .1256443
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}  .906283{col 30}{space 2} .0445301{col 41}{space 1}   20.35{col 50}{space 3}0.000{col 58}{space 4}  .818833{col 71}{space 3}  .993733
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.1397081{col 30}{space 2}  .057628{col 41}{space 1}   -2.42{col 50}{space 3}0.016{col 58}{space 4}-.2528804{col 71}{space 3}-.0265359
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0034148{col 30}{space 2}   .01597{col 41}{space 1}   -0.21{col 50}{space 3}0.831{col 58}{space 4}-.0347773{col 71}{space 3} .0279476
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0245767{col 30}{space 2} .0406888{col 41}{space 1}    0.60{col 50}{space 3}0.546{col 58}{space 4}-.0553295{col 71}{space 3}  .104483
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0114586{col 30}{space 2} .0220604{col 41}{space 1}    0.52{col 50}{space 3}0.604{col 58}{space 4}-.0318644{col 71}{space 3} .0547817
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0078559{col 30}{space 2} .0027413{col 41}{space 1}   -2.87{col 50}{space 3}0.004{col 58}{space 4}-.0132393{col 71}{space 3}-.0024724
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0126794{col 30}{space 2} .0138234{col 41}{space 1}    0.92{col 50}{space 3}0.359{col 58}{space 4}-.0144676{col 71}{space 3} .0398265
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0510245{col 30}{space 2} .0520117{col 41}{space 1}   -0.98{col 50}{space 3}0.327{col 58}{space 4}-.1531672{col 71}{space 3} .0511182
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0655834{col 30}{space 2} .0350867{col 41}{space 1}   -1.87{col 50}{space 3}0.062{col 58}{space 4}-.1344881{col 71}{space 3} .0033214
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1905875{col 30}{space 2} .0547043{col 41}{space 1}    3.48{col 50}{space 3}0.001{col 58}{space 4} .0831569{col 71}{space 3} .2980182
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,726
                                                {txt}F(11, 606)        =  {res}     6.53
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0779
                                                {txt}Root MSE          =    {res} .25068

{txt}{ralign 82:(Std. err. adjusted for {res:607} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}             fb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.1396671{col 30}{space 2} .0180283{col 41}{space 1}   -7.75{col 50}{space 3}0.000{col 58}{space 4}-.1750726{col 71}{space 3}-.1042616
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0082887{col 30}{space 2} .0279532{col 41}{space 1}   -0.30{col 50}{space 3}0.767{col 58}{space 4}-.0631856{col 71}{space 3} .0466083
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1033681{col 30}{space 2} .0504071{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.2023619{col 71}{space 3}-.0043744
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0468543{col 30}{space 2} .0330617{col 41}{space 1}    1.42{col 50}{space 3}0.157{col 58}{space 4}-.0180751{col 71}{space 3} .1117837
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0004242{col 30}{space 2} .0105318{col 41}{space 1}    0.04{col 50}{space 3}0.968{col 58}{space 4} -.020259{col 71}{space 3} .0211075
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0225211{col 30}{space 2} .0216264{col 41}{space 1}   -1.04{col 50}{space 3}0.298{col 58}{space 4}-.0649929{col 71}{space 3} .0199507
{txt}{space 10}center {c |}{col 18}{res}{space 2}-.0028529{col 30}{space 2} .0170901{col 41}{space 1}   -0.17{col 50}{space 3}0.867{col 58}{space 4}-.0364159{col 71}{space 3} .0307102
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0014812{col 30}{space 2} .0035675{col 41}{space 1}   -0.42{col 50}{space 3}0.678{col 58}{space 4}-.0084873{col 71}{space 3} .0055249
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0294254{col 30}{space 2} .0139702{col 41}{space 1}    2.11{col 50}{space 3}0.036{col 58}{space 4} .0019896{col 71}{space 3} .0568612
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0053989{col 30}{space 2} .0727627{col 41}{space 1}   -0.07{col 50}{space 3}0.941{col 58}{space 4}-.1482966{col 71}{space 3} .1374987
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0078363{col 30}{space 2} .0210087{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.0490951{col 71}{space 3} .0334225
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1060408{col 30}{space 2}  .029978{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0471674{col 71}{space 3} .1649142
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,726}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:607}
{txt}{col 53}{lalign 17:F({res:10}, {res:606})}{col 70} = {res}{ralign 6:2.39}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0088}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.5244}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.2601}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2238}

{txt}{ralign 82:(Std. err. adjusted for {res:607} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}             fb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.1265923{col 30}{space 2} .0299977{col 41}{space 1}   -4.22{col 50}{space 3}0.000{col 58}{space 4}-.1855044{col 71}{space 3}-.0676803
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0167558{col 30}{space 2} .0786084{col 41}{space 1}   -0.21{col 50}{space 3}0.831{col 58}{space 4}-.1711337{col 71}{space 3} .1376222
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .1225564{col 30}{space 2} .1053111{col 41}{space 1}    1.16{col 50}{space 3}0.245{col 58}{space 4}-.0842626{col 71}{space 3} .3293754
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} -.039115{col 30}{space 2} .0309434{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-.0998843{col 71}{space 3} .0216543
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0225873{col 30}{space 2} .0505499{col 41}{space 1}    0.45{col 50}{space 3}0.655{col 58}{space 4} -.076687{col 71}{space 3} .1218615
{txt}{space 10}center {c |}{col 18}{res}{space 2} -.011466{col 30}{space 2} .0427085{col 41}{space 1}   -0.27{col 50}{space 3}0.788{col 58}{space 4}-.0953407{col 71}{space 3} .0724086
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0086537{col 30}{space 2} .0076613{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.0236997{col 71}{space 3} .0063923
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}  .014922{col 30}{space 2} .0307398{col 41}{space 1}    0.49{col 50}{space 3}0.628{col 58}{space 4}-.0454474{col 71}{space 3} .0752914
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0654155{col 30}{space 2} .1002034{col 41}{space 1}    0.65{col 50}{space 3}0.514{col 58}{space 4}-.1313725{col 71}{space 3} .2622035
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}  .014626{col 30}{space 2} .0352639{col 41}{space 1}    0.41{col 50}{space 3}0.678{col 58}{space 4}-.0546283{col 71}{space 3} .0838803
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1299319{col 30}{space 2} .0710408{col 41}{space 1}    1.83{col 50}{space 3}0.068{col 58}{space 4}-.0095842{col 71}{space 3}  .269448
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,684
                                                {txt}{help j_robustsingular:F(10, 607) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0328
                                                {txt}Root MSE          =    {res} .23922

{txt}{ralign 82:(Std. err. adjusted for {res:608} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            nfb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0243023{col 30}{space 2} .0133684{col 41}{space 1}   -1.82{col 50}{space 3}0.070{col 58}{space 4}-.0505561{col 71}{space 3} .0019516
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0147253{col 30}{space 2} .0259062{col 41}{space 1}    0.57{col 50}{space 3}0.570{col 58}{space 4}-.0361513{col 71}{space 3} .0656019
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0727729{col 30}{space 2} .0166778{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.1055261{col 71}{space 3}-.0400197
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} -.024405{col 30}{space 2} .0217022{col 41}{space 1}   -1.12{col 50}{space 3}0.261{col 58}{space 4}-.0670256{col 71}{space 3} .0182155
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0107155{col 30}{space 2} .0052268{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.0209803{col 71}{space 3}-.0004507
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0072471{col 30}{space 2} .0145575{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.0213421{col 71}{space 3} .0358363
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0176452{col 30}{space 2}  .010523{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0030208{col 71}{space 3} .0383111
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0015762{col 30}{space 2}  .001047{col 41}{space 1}    1.51{col 50}{space 3}0.133{col 58}{space 4}-.0004799{col 71}{space 3} .0036323
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0496743{col 30}{space 2} .0082775{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .0334182{col 71}{space 3} .0659304
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0116686{col 30}{space 2} .0500642{col 41}{space 1}    0.23{col 50}{space 3}0.816{col 58}{space 4}-.0866515{col 71}{space 3} .1099887
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}  -.03539{col 30}{space 2} .0223199{col 41}{space 1}   -1.59{col 50}{space 3}0.113{col 58}{space 4}-.0792235{col 71}{space 3} .0084436
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0001569{col 30}{space 2}  .023922{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.0471368{col 71}{space 3} .0468229
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,684}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:608}
{txt}{col 53}{lalign 17:F({res:10}, {res:607})}{col 70} = {res}{ralign 6:5.34}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2121}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0926}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2314}

{txt}{ralign 82:(Std. err. adjusted for {res:608} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            nfb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}  .007398{col 30}{space 2} .0177984{col 41}{space 1}    0.42{col 50}{space 3}0.678{col 58}{space 4}-.0275558{col 71}{space 3} .0423519
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0034162{col 30}{space 2} .0617126{col 41}{space 1}   -0.06{col 50}{space 3}0.956{col 58}{space 4}-.1246122{col 71}{space 3} .1177799
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.1086945{col 30}{space 2} .0534505{col 41}{space 1}   -2.03{col 50}{space 3}0.042{col 58}{space 4}-.2136649{col 71}{space 3}-.0037242
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0084523{col 30}{space 2}  .013843{col 41}{space 1}   -0.61{col 50}{space 3}0.542{col 58}{space 4}-.0356383{col 71}{space 3} .0187337
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0034962{col 30}{space 2} .0383788{col 41}{space 1}    0.09{col 50}{space 3}0.927{col 58}{space 4}-.0718751{col 71}{space 3} .0788676
{txt}{space 10}center {c |}{col 18}{res}{space 2} .0129313{col 30}{space 2} .0226576{col 41}{space 1}    0.57{col 50}{space 3}0.568{col 58}{space 4}-.0315656{col 71}{space 3} .0574281
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0069263{col 30}{space 2} .0024688{col 41}{space 1}   -2.81{col 50}{space 3}0.005{col 58}{space 4}-.0117746{col 71}{space 3}-.0020779
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0138477{col 30}{space 2} .0124379{col 41}{space 1}    1.11{col 50}{space 3}0.266{col 58}{space 4}-.0105787{col 71}{space 3} .0382742
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0087003{col 30}{space 2} .0500682{col 41}{space 1}   -0.17{col 50}{space 3}0.862{col 58}{space 4}-.1070282{col 71}{space 3} .0896276
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0279528{col 30}{space 2} .0283695{col 41}{space 1}   -0.99{col 50}{space 3}0.325{col 58}{space 4}-.0836671{col 71}{space 3} .0277614
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   .13962{col 30}{space 2}  .050222{col 41}{space 1}    2.78{col 50}{space 3}0.006{col 58}{space 4} .0409901{col 71}{space 3} .2382499
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         *Continue table
.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v_donate_15any' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_15any',`fuci_donate_15any'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}. 
.         tex Electoral victory (FE) & `fb1f_donate_15any' & `fb1f_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_vf_donate_15any' & `fp_vf_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flcif_donate_15any',`fucif_donate_15any'] & [`flcif_b5',`fucif_b5']  \\
{res}{txt}
{com}.         tex & & \\
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' \\
{res}{txt}
{com}.         
.         tex & & \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}. 
.                 tex Electoral victory & `nfb1_donate_15any' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfp_v_donate_15any' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_15any',`nfuci_donate_15any'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Electoral victory (FE) & `nfb1f_donate_15any' & `nfb1f_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfp_vf_donate_15any' & `nfp_vf_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflcif_donate_15any',`nfucif_donate_15any'] & [`nflcif_b5',`nfucif_b5']  \\
{res}{txt}
{com}.         tex & & \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_15any' & `nfN_b5' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_15any' & `nfmean_b5' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on donating in the next election. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, and non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG8.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. keep if rank==1|rank==2|rank==3
{txt}(0 observations deleted)

{com}. drop if rank==.
{txt}(0 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(270 real changes made, 270 to missing)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if rank==1
{txt}(4,263 real changes made)

{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG8.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG8.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG8.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations comparison with third-placed candidate (donor-level){c )-}\label{c -(}tab:donations_d_ols1_3{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Mayor & Other races \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.         
.         
.                 
.                 *No Family
.                 *Regressions
.                 quietly: regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_102 contraloria above_lim if (rank==1|rank==3),vce(cluster muni_code)
{txt}  3{com}.                 quietly sum `var' if e(sample)
{txt}  4{com}.                         local mean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local sd_`var' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 regress `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_102 contraloria above_lim if (rank==1|rank==3),vce(cluster muni_code)
{txt}  7{com}. 
.                 local N_`var' : di %5.0f e(N)
{txt}  8{com}. 
.                 matrix b = e(b)
{txt}  9{com}.                 matrix v = e(V)
{txt} 10{com}.                 matrix res=r(table)
{txt} 11{com}.                 
.                 local b1_`var' : di %5.3f b[1,1]
{txt} 12{com}.                 local se1_`var' : di %5.3f sqrt(v[1,1])
{txt} 13{com}.                 local p_v_`var' :di %5.3f res[4,1]
{txt} 14{com}.                 local uci_`var': di %5.3f res[6,1]
{txt} 15{com}.                 local lci_`var': di %5.3f res[5,1]
{txt} 16{com}.                 
.                 areg `var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 17{com}. 
.                 local Nf_`var' : di %5.0f e(N)
{txt} 18{com}. 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local b1f_`var' : di %5.3f bf[1,1]
{txt} 22{com}.                 local se1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local p_vf_`var' :di %5.3f resf[4,1]
{txt} 24{com}.                 local ucif_`var': di %5.3f resf[6,1]
{txt} 25{com}.                 local lcif_`var': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     4,199
                                                {txt}{help j_robustsingular:F(9, 610) }        =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0231
                                                {txt}Root MSE          =    {res} .27847

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0060784{col 30}{space 2} .0145917{col 41}{space 1}   -0.42{col 50}{space 3}0.677{col 58}{space 4}-.0347344{col 71}{space 3} .0225777
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0151933{col 30}{space 2} .0276395{col 41}{space 1}    0.55{col 50}{space 3}0.583{col 58}{space 4}-.0390869{col 71}{space 3} .0694735
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .9335491{col 30}{space 2}  .017987{col 41}{space 1}   51.90{col 50}{space 3}0.000{col 58}{space 4} .8982251{col 71}{space 3}  .968873
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0143641{col 30}{space 2}  .032051{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.0773079{col 71}{space 3} .0485796
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0056883{col 30}{space 2} .0060725{col 41}{space 1}   -0.94{col 50}{space 3}0.349{col 58}{space 4}-.0176139{col 71}{space 3} .0062373
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0068327{col 30}{space 2} .0164043{col 41}{space 1}    0.42{col 50}{space 3}0.677{col 58}{space 4} -.025383{col 71}{space 3} .0390485
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}  .001922{col 30}{space 2} .0009729{col 41}{space 1}    1.98{col 50}{space 3}0.049{col 58}{space 4} .0000113{col 71}{space 3} .0038327
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0479532{col 30}{space 2}  .009152{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4}   .02998{col 71}{space 3} .0659264
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0326028{col 30}{space 2} .0464771{col 41}{space 1}   -0.70{col 50}{space 3}0.483{col 58}{space 4}-.1238774{col 71}{space 3} .0586718
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0217003{col 30}{space 2} .0273043{col 41}{space 1}   -0.79{col 50}{space 3}0.427{col 58}{space 4}-.0753222{col 71}{space 3} .0319216
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0199187{col 30}{space 2} .0279404{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4}-.0349524{col 71}{space 3} .0747898
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,199}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:611}
{txt}{col 53}{lalign 17:F({res:9}, {res:610})}{col 70} = {res}{ralign 6:2.23}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0191}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2229}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0885}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2687}

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    donate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0061414{col 30}{space 2} .0225822{col 41}{space 1}    0.27{col 50}{space 3}0.786{col 58}{space 4}-.0382069{col 71}{space 3} .0504897
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0109386{col 30}{space 2} .0390977{col 41}{space 1}   -0.28{col 50}{space 3}0.780{col 58}{space 4}-.0877211{col 71}{space 3} .0658439
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .0028207{col 30}{space 2} .0684036{col 41}{space 1}    0.04{col 50}{space 3}0.967{col 58}{space 4}-.1315144{col 71}{space 3} .1371557
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}  .020627{col 30}{space 2} .0157111{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0102274{col 71}{space 3} .0514814
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0726013{col 30}{space 2} .0385189{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.1482471{col 71}{space 3} .0030444
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0069604{col 30}{space 2} .0034174{col 41}{space 1}   -2.04{col 50}{space 3}0.042{col 58}{space 4}-.0136716{col 71}{space 3}-.0002491
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0093076{col 30}{space 2} .0160543{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0222208{col 71}{space 3} .0408359
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0506639{col 30}{space 2} .0330728{col 41}{space 1}   -1.53{col 50}{space 3}0.126{col 58}{space 4}-.1156142{col 71}{space 3} .0142863
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0246472{col 30}{space 2}  .032487{col 41}{space 1}   -0.76{col 50}{space 3}0.448{col 58}{space 4}-.0884471{col 71}{space 3} .0391528
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1313114{col 30}{space 2} .0487243{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0356237{col 71}{space 3} .2269991
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res}     4,055
                                                {txt}F(9, 599)         =  {res}     6.52
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0323
                                                {txt}Root MSE          =    {res} .22311

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0098558{col 30}{space 2} .0131991{col 41}{space 1}   -0.75{col 50}{space 3}0.456{col 58}{space 4} -.035778{col 71}{space 3} .0160665
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0011312{col 30}{space 2} .0228225{col 41}{space 1}    0.05{col 50}{space 3}0.960{col 58}{space 4}-.0436906{col 71}{space 3}  .045953
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0012168{col 30}{space 2} .0282467{col 41}{space 1}   -0.04{col 50}{space 3}0.966{col 58}{space 4}-.0566915{col 71}{space 3} .0542579
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} -.010477{col 30}{space 2}  .005726{col 41}{space 1}   -1.83{col 50}{space 3}0.068{col 58}{space 4}-.0217224{col 71}{space 3} .0007684
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0167542{col 30}{space 2} .0133852{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.0095334{col 71}{space 3} .0430418
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0019179{col 30}{space 2} .0006714{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0005993{col 71}{space 3} .0032366
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0485919{col 30}{space 2} .0083857{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .0321231{col 71}{space 3} .0650608
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0001574{col 30}{space 2} .0463615{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.0912082{col 71}{space 3} .0908934
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.025284{col 30}{space 2} .0250583{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.0744968{col 71}{space 3} .0239289
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0178927{col 30}{space 2} .0234002{col 41}{space 1}   -0.76{col 50}{space 3}0.445{col 58}{space 4}-.0638492{col 71}{space 3} .0280637
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,055}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:600}
{txt}{col 53}{lalign 17:F({res:9}, {res:599})}{col 70} = {res}{ralign 6:2.73}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0040}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2324}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0970}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2153}

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              b5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.014536{col 30}{space 2} .0188622{col 41}{space 1}   -0.77{col 50}{space 3}0.441{col 58}{space 4}  -.05158{col 71}{space 3}  .022508
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0269805{col 30}{space 2} .0368802{col 41}{space 1}   -0.73{col 50}{space 3}0.465{col 58}{space 4}-.0994107{col 71}{space 3} .0454496
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0057715{col 30}{space 2}   .06941{col 41}{space 1}   -0.08{col 50}{space 3}0.934{col 58}{space 4}-.1420881{col 71}{space 3} .1305451
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0218903{col 30}{space 2} .0168394{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.0111811{col 71}{space 3} .0549616
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0472821{col 30}{space 2} .0356229{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.1172431{col 71}{space 3} .0226789
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0053609{col 30}{space 2} .0031551{col 41}{space 1}   -1.70{col 50}{space 3}0.090{col 58}{space 4}-.0115573{col 71}{space 3} .0008356
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .0212071{col 30}{space 2} .0138181{col 41}{space 1}    1.53{col 50}{space 3}0.125{col 58}{space 4}-.0059307{col 71}{space 3} .0483448
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} -.031726{col 30}{space 2} .0318511{col 41}{space 1}   -1.00{col 50}{space 3}0.320{col 58}{space 4}-.0942794{col 71}{space 3} .0308275
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0404381{col 30}{space 2} .0304813{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.1003013{col 71}{space 3} .0194251
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  .084119{col 30}{space 2} .0437544{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0018117{col 71}{space 3} .1700496
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
. 
.         *Continue table
.         tex Runner-up & `b1_donate_15any' & `b1_b5' & `b1_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_15any' & `p_v_b5' & `p_v_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_15any',`uci_donate_15any'] & [`lci_b5',`uci_b5'] & [`lci_b2b',`uci_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         tex Runner-up (FE) & `b1f_donate_15any' & `b1f_b5' & `b1f_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_vf_donate_15any' & `p_vf_b5' & `p_vf_b2b' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lcif_donate_15any',`ucif_donate_15any'] & [`lcif_b5',`uci_b5'] & [`lcif_b2b',`ucif_b2b'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         
.         tex Observations & `N_donate_15any' & `N_b5' & `N_b2b' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_15any' & `mean_b5' & `mean_b2b' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on donating in the next election. Sample includes donors of winner and third-placed candidate. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, party is not left-wing or right-wing, and non family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all family and non family donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG9.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. 
. 
. keep if rank==1|rank==2|rank==3
{txt}(0 observations deleted)

{com}. drop if rank==.
{txt}(0 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(270 real changes made, 270 to missing)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if rank==1
{txt}(4,263 real changes made)

{com}. 
. 
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(2,365 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(6,166 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(2,365 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(6,166 missing values generated)

{com}. gen nfruns_any = runs_any if family==0
{txt}(2,365 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(6,166 missing values generated)

{com}. gen nfgot_above_ext = got_above_ext if family==0
{txt}(2,370 missing values generated)

{com}. gen fgot_above_ext = got_above_ext if family==1
{txt}(6,166 missing values generated)

{com}. 
. 
. 
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG9.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG9.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG9.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[h]
{res}{txt}
{com}.         tex \caption{c -(}Effect of electoral victory on benefits to donors comparison with third-placed candidate (donor-level){c )-}\label{c -(}tab:table_benefits_ols1_3{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c{c )-} \hline
{res}{txt}
{com}.         tex Outcome:& \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Total contracts{c )-}&\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}Receive contract{c )-}&Receive contract& Runs in 2015\\
{res}{txt}
{com}.         tex &  \multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} &\multicolumn{c -(}2{c )-}{c -(}c{c )-}{c -(}(municipality){c )-} & (outside)& \\
{res}{txt}
{com}.         tex & Non-Family &Family & Non-Family &Family  & Family &Family \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4)& (5) & (6)\\ \hline
{res}{txt}
{com}.         tex & & & & & &\\
{res}{txt}
{com}.         
.         *preserve
.         *drop contract
.         *rename got_any contract
.         
.         *Model 1
.         foreach x in  total_cont_num_d contract{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d rank_don_alt_all lcont_donor_102 contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  3{com}.                 quietly sum nf`x' if e(sample)
{txt}  4{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local nfsd_`x' : di %5.3f r(sd)                 
{txt}  6{com}.                 
.                 regress nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d rank_don_alt_all lcont_donor_102 contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  7{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
. 
.                 areg nf`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_102 contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}.         
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local nfb1f_`x' : di %5.3f bf[1,1]
{txt} 22{com}.                 local nfse1f_`x' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local nfp_vf_`x' :di %5.3f resf[4,1]
{txt} 24{com}.                 local nfucif_`x': di %5.3f resf[6,1]
{txt} 25{com}.                 local nflcif_`x': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     4,199
                                                {txt}{help j_robustsingular:F(9, 610) }        =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0087
                                                {txt}Root MSE          =    {res} 4.1615

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}nftotal_cont_n~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .7711633{col 30}{space 2} .1233723{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .5288772{col 71}{space 3} 1.013449
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0604587{col 30}{space 2}   .24547{col 41}{space 1}   -0.25{col 50}{space 3}0.806{col 58}{space 4}-.5425275{col 71}{space 3} .4216101
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.9425975{col 30}{space 2} .1883839{col 41}{space 1}   -5.00{col 50}{space 3}0.000{col 58}{space 4}-1.312557{col 71}{space 3}-.5726379
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.1334509{col 30}{space 2} .3190004{col 41}{space 1}   -0.42{col 50}{space 3}0.676{col 58}{space 4}-.7599231{col 71}{space 3} .4930214
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0599408{col 30}{space 2}  .095305{col 41}{space 1}    0.63{col 50}{space 3}0.530{col 58}{space 4}-.1272249{col 71}{space 3} .2471065
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .1923166{col 30}{space 2}   .20747{col 41}{space 1}    0.93{col 50}{space 3}0.354{col 58}{space 4}-.2151255{col 71}{space 3} .5997587
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0006601{col 30}{space 2} .0276471{col 41}{space 1}   -0.02{col 50}{space 3}0.981{col 58}{space 4}-.0549552{col 71}{space 3}  .053635
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.1282969{col 30}{space 2} .1011613{col 41}{space 1}   -1.27{col 50}{space 3}0.205{col 58}{space 4}-.3269635{col 71}{space 3} .0703697
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.7278224{col 30}{space 2} .1432283{col 41}{space 1}   -5.08{col 50}{space 3}0.000{col 58}{space 4}-1.009103{col 71}{space 3} -.446542
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.1316506{col 30}{space 2} .2169143{col 41}{space 1}   -0.61{col 50}{space 3}0.544{col 58}{space 4}  -.55764{col 71}{space 3} .2943388
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3104902{col 30}{space 2} .2173823{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.1164183{col 71}{space 3} .7373988
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,199}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:611}
{txt}{col 53}{lalign 17:F({res:9}, {res:610})}{col 70} = {res}{ralign 6:5.06}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.1498}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0027}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:4.1691}

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}nftotal_cont_n~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .6675346{col 30}{space 2} .1605219{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4}  .352292{col 71}{space 3} .9827772
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.1989928{col 30}{space 2} .2464357{col 41}{space 1}   -0.81{col 50}{space 3}0.420{col 58}{space 4}-.6829583{col 71}{space 3} .2849726
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.9455153{col 30}{space 2}  .428566{col 41}{space 1}   -2.21{col 50}{space 3}0.028{col 58}{space 4}-1.787159{col 71}{space 3}-.1038714
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .1454988{col 30}{space 2} .1537778{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.1564995{col 71}{space 3}  .447497
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}  .048642{col 30}{space 2} .3125752{col 41}{space 1}    0.16{col 50}{space 3}0.876{col 58}{space 4} -.565212{col 71}{space 3} .6624961
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0254024{col 30}{space 2} .0449689{col 41}{space 1}    0.56{col 50}{space 3}0.572{col 58}{space 4}-.0629102{col 71}{space 3}  .113715
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2} .1874346{col 30}{space 2} .1273904{col 41}{space 1}    1.47{col 50}{space 3}0.142{col 58}{space 4}-.0627423{col 71}{space 3} .4376116
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.4972453{col 30}{space 2} .1858393{col 41}{space 1}   -2.68{col 50}{space 3}0.008{col 58}{space 4}-.8622078{col 71}{space 3}-.1322828
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.2439326{col 30}{space 2} .3622578{col 41}{space 1}   -0.67{col 50}{space 3}0.501{col 58}{space 4}-.9553565{col 71}{space 3} .4674912
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3111081{col 30}{space 2} .3075745{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.2929254{col 71}{space 3} .9151415
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,199
                                                {txt}{help j_robustsingular:F(9, 610) }        =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0280
                                                {txt}Root MSE          =    {res} .31241

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}      nfcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0961364{col 30}{space 2} .0118212{col 41}{space 1}    8.13{col 50}{space 3}0.000{col 58}{space 4} .0729212{col 71}{space 3} .1193516
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}  .023463{col 30}{space 2} .0348442{col 41}{space 1}    0.67{col 50}{space 3}0.501{col 58}{space 4}-.0449661{col 71}{space 3} .0918921
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.1542005{col 30}{space 2} .0168435{col 41}{space 1}   -9.15{col 50}{space 3}0.000{col 58}{space 4}-.1872787{col 71}{space 3}-.1211222
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0065503{col 30}{space 2}  .028126{col 41}{space 1}   -0.23{col 50}{space 3}0.816{col 58}{space 4}-.0617858{col 71}{space 3} .0486852
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0196759{col 30}{space 2} .0123301{col 41}{space 1}    1.60{col 50}{space 3}0.111{col 58}{space 4}-.0045386{col 71}{space 3} .0438904
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0217117{col 30}{space 2} .0214548{col 41}{space 1}   -1.01{col 50}{space 3}0.312{col 58}{space 4} -.063846{col 71}{space 3} .0204225
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} -.001213{col 30}{space 2} .0023445{col 41}{space 1}   -0.52{col 50}{space 3}0.605{col 58}{space 4}-.0058173{col 71}{space 3} .0033912
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.0318118{col 30}{space 2} .0134477{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.0582211{col 71}{space 3}-.0054024
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0688038{col 30}{space 2}  .043864{col 41}{space 1}   -1.57{col 50}{space 3}0.117{col 58}{space 4}-.1549465{col 71}{space 3}  .017339
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0165925{col 30}{space 2} .0214373{col 41}{space 1}   -0.77{col 50}{space 3}0.439{col 58}{space 4}-.0586923{col 71}{space 3} .0255073
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0935209{col 30}{space 2}  .022108{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .0501039{col 71}{space 3} .1369379
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,199}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:611}
{txt}{col 53}{lalign 17:F({res:9}, {res:610})}{col 70} = {res}{ralign 6:7.79}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2309}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0979}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.3006}

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}      nfcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0930844{col 30}{space 2} .0156435{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .0623627{col 71}{space 3} .1238061
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0286066{col 30}{space 2} .0397824{col 41}{space 1}   -0.72{col 50}{space 3}0.472{col 58}{space 4}-.1067337{col 71}{space 3} .0495206
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0708987{col 30}{space 2} .0424339{col 41}{space 1}   -1.67{col 50}{space 3}0.095{col 58}{space 4}-.1542329{col 71}{space 3} .0124355
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0274312{col 30}{space 2}   .01879{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0094698{col 71}{space 3} .0643322
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0500857{col 30}{space 2} .0302066{col 41}{space 1}   -1.66{col 50}{space 3}0.098{col 58}{space 4}-.1094073{col 71}{space 3} .0092359
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0024789{col 30}{space 2} .0024972{col 41}{space 1}    0.99{col 50}{space 3}0.321{col 58}{space 4}-.0024253{col 71}{space 3} .0073831
{txt}{space 1}lcont_donor_102 {c |}{col 18}{res}{space 2}-.0073776{col 30}{space 2} .0197637{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.0461907{col 71}{space 3} .0314354
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0718802{col 30}{space 2} .0503474{col 41}{space 1}   -1.43{col 50}{space 3}0.154{col 58}{space 4}-.1707556{col 71}{space 3} .0269951
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0220103{col 30}{space 2} .0342572{col 41}{space 1}   -0.64{col 50}{space 3}0.521{col 58}{space 4}-.0892866{col 71}{space 3} .0452659
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0941184{col 30}{space 2} .0377167{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4}  .020048{col 71}{space 3} .1681889
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. 
. keep if rank==1|rank==2|rank==3
{txt}(0 observations deleted)

{com}. drop if rank==.
{txt}(0 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(270 real changes made, 270 to missing)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if rank==1
{txt}(4,263 real changes made)

{com}. 
. 
. gen nftotal_cont_num_d = total_cont_num_d if family==0
{txt}(2,365 missing values generated)

{com}. gen ftotal_cont_num_d = total_cont_num_d if family==1
{txt}(6,166 missing values generated)

{com}. gen nfcontract = contract if family==0
{txt}(2,365 missing values generated)

{com}. gen fcontract = contract if family==1
{txt}(6,166 missing values generated)

{com}. gen nfruns_any = runs_any if family==0
{txt}(2,365 missing values generated)

{com}. gen fruns_any = runs_any if family==1
{txt}(6,166 missing values generated)

{com}. gen nfgot_above_ext = got_above_ext if family==0
{txt}(2,370 missing values generated)

{com}. gen fgot_above_ext = got_above_ext if family==1
{txt}(6,166 missing values generated)

{com}. 
. 
.         
.         foreach x in  total_cont_num_d contract got_above_ext runs_any{c -(}
{txt}  2{com}.         
.                 *No Family
.                 *Regressions
.                 quietly: regress f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`x' if e(sample)
{txt}  4{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`x' : di %5.3f r(sd)          
{txt}  6{com}.                 
.                 regress f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 13{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 15{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 16{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 17{com}.                 
.                 areg f`x' treat sanc_before ilegal p_prop elec_exp pol_exp_d rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}.                 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local fb1f_`x' : di %5.3f bf[1,1]
{txt} 22{com}.                 local fse1f_`x' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local fp_vf_`x' :di %5.3f resf[4,1]
{txt} 24{com}.                 local fucif_`x': di %5.3f resf[6,1]
{txt} 25{com}.                 local flcif_`x': di %5.3f resf[5,1]
{txt} 26{com}.                 
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,579
                                                {txt}F(10, 602)        =  {res}     0.55
                                                {txt}Prob > F          = {res}    0.8512
                                                {txt}R-squared         = {res}    0.0070
                                                {txt}Root MSE          =    {res} .24624

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}ftotal_cont_nu~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.031568{col 30}{space 2} .0186191{col 41}{space 1}   -1.70{col 50}{space 3}0.091{col 58}{space 4}-.0681342{col 71}{space 3} .0049983
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0053807{col 30}{space 2} .0033317{col 41}{space 1}   -1.62{col 50}{space 3}0.107{col 58}{space 4}-.0119238{col 71}{space 3} .0011623
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0013661{col 30}{space 2} .0145799{col 41}{space 1}    0.09{col 50}{space 3}0.925{col 58}{space 4}-.0272677{col 71}{space 3} .0299998
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0363409{col 30}{space 2}  .025273{col 41}{space 1}   -1.44{col 50}{space 3}0.151{col 58}{space 4}-.0859748{col 71}{space 3}  .013293
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0005057{col 30}{space 2}  .001232{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-.0029253{col 71}{space 3} .0019138
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0128936{col 30}{space 2} .0102845{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.0330915{col 71}{space 3} .0073042
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0006808{col 30}{space 2} .0036101{col 41}{space 1}   -0.19{col 50}{space 3}0.850{col 58}{space 4}-.0077707{col 71}{space 3} .0064092
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0079572{col 30}{space 2} .0062989{col 41}{space 1}    1.26{col 50}{space 3}0.207{col 58}{space 4}-.0044133{col 71}{space 3} .0203277
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}  -.00289{col 30}{space 2} .0063373{col 41}{space 1}   -0.46{col 50}{space 3}0.649{col 58}{space 4}-.0153358{col 71}{space 3} .0095558
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.028272{col 30}{space 2} .0178414{col 41}{space 1}   -1.58{col 50}{space 3}0.114{col 58}{space 4} -.063311{col 71}{space 3} .0067669
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0425323{col 30}{space 2} .0344015{col 41}{space 1}    1.24{col 50}{space 3}0.217{col 58}{space 4}-.0250293{col 71}{space 3} .1100939
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,579}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:603}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(9, 602)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.4550}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1097}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2323}

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}ftotal_cont_nu~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0228355{col 30}{space 2}  .019546{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-.0612221{col 71}{space 3} .0155512
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0417643{col 30}{space 2}  .044376{col 41}{space 1}   -0.94{col 50}{space 3}0.347{col 58}{space 4}-.1289148{col 71}{space 3} .0453863
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0516313{col 30}{space 2}  .077315{col 41}{space 1}    0.67{col 50}{space 3}0.505{col 58}{space 4}-.1002086{col 71}{space 3} .2034713
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0502517{col 30}{space 2} .0994099{col 41}{space 1}   -0.51{col 50}{space 3}0.613{col 58}{space 4} -.245484{col 71}{space 3} .1449805
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0175536{col 30}{space 2}  .024342{col 41}{space 1}   -0.72{col 50}{space 3}0.471{col 58}{space 4}-.0653592{col 71}{space 3}  .030252
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0285663{col 30}{space 2} .0269956{col 41}{space 1}    1.06{col 50}{space 3}0.290{col 58}{space 4}-.0244507{col 71}{space 3} .0815833
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0012403{col 30}{space 2} .0108566{col 41}{space 1}    0.11{col 50}{space 3}0.909{col 58}{space 4} -.020081{col 71}{space 3} .0225617
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0314977{col 30}{space 2} .0455862{col 41}{space 1}    0.69{col 50}{space 3}0.490{col 58}{space 4}-.0580296{col 71}{space 3}  .121025
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0001692{col 30}{space 2} .0161466{col 41}{space 1}   -0.01{col 50}{space 3}0.992{col 58}{space 4}-.0318797{col 71}{space 3} .0315413
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0456318{col 30}{space 2} .0351973{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-.1147562{col 71}{space 3} .0234926
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0108591{col 30}{space 2} .1031814{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.2134983{col 71}{space 3}   .19178
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,579
                                                {txt}F(10, 602)        =  {res}     0.91
                                                {txt}Prob > F          = {res}    0.5276
                                                {txt}R-squared         = {res}    0.0094
                                                {txt}Root MSE          =    {res} .07923

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0119043{col 30}{space 2} .0055455{col 41}{space 1}   -2.15{col 50}{space 3}0.032{col 58}{space 4}-.0227953{col 71}{space 3}-.0010133
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0040808{col 30}{space 2} .0020846{col 41}{space 1}   -1.96{col 50}{space 3}0.051{col 58}{space 4}-.0081747{col 71}{space 3} .0000131
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}  .000948{col 30}{space 2} .0059255{col 41}{space 1}    0.16{col 50}{space 3}0.873{col 58}{space 4}-.0106891{col 71}{space 3} .0125851
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0132881{col 30}{space 2} .0077109{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4}-.0284315{col 71}{space 3} .0018553
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0007427{col 30}{space 2} .0006818{col 41}{space 1}   -1.09{col 50}{space 3}0.276{col 58}{space 4}-.0020816{col 71}{space 3} .0005962
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0032936{col 30}{space 2} .0048615{col 41}{space 1}   -0.68{col 50}{space 3}0.498{col 58}{space 4}-.0128411{col 71}{space 3} .0062539
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0004503{col 30}{space 2} .0015304{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.0025552{col 71}{space 3} .0034559
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0038677{col 30}{space 2} .0043261{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4}-.0046284{col 71}{space 3} .0123637
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} -.002597{col 30}{space 2} .0028277{col 41}{space 1}   -0.92{col 50}{space 3}0.359{col 58}{space 4}-.0081504{col 71}{space 3} .0029564
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0105693{col 30}{space 2} .0064994{col 41}{space 1}   -1.63{col 50}{space 3}0.104{col 58}{space 4}-.0233336{col 71}{space 3}  .002195
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0139841{col 30}{space 2} .0105383{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0067122{col 71}{space 3} .0346803
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 52}{lalign 17:Number of obs}{col 69} = {res}{ralign 7:1,579}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 52}{lalign 17:No. of categories}{col 69} = {res}{ralign 7:603}
{txt}{col 52}{lalign 17:{help j_robustsingular##|_new:F(9, 602)}}{col 69} = {res}{ralign 7:.}
{txt}{col 52}{lalign 17:Prob > F}{col 69} = {res}{ralign 7:.}
{txt}{col 52}{lalign 17:R-squared}{col 69} = {res}{ralign 7:0.2943}
{txt}{col 52}{lalign 17:Adj R-squared}{col 69} = {res}{ralign 7:-0.1527}
{txt}{col 52}{lalign 17:Root MSE}{col 69} = {res}{ralign 7:0.0852}

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fcontract{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0111762{col 30}{space 2} .0121433{col 41}{space 1}   -0.92{col 50}{space 3}0.358{col 58}{space 4}-.0350246{col 71}{space 3} .0126723
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0295484{col 30}{space 2} .0357897{col 41}{space 1}   -0.83{col 50}{space 3}0.409{col 58}{space 4}-.0998362{col 71}{space 3} .0407394
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0020554{col 30}{space 2} .0513513{col 41}{space 1}    0.04{col 50}{space 3}0.968{col 58}{space 4} -.098794{col 71}{space 3} .1029048
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0338956{col 30}{space 2} .0675062{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.1664718{col 71}{space 3} .0986806
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0180005{col 30}{space 2}  .022913{col 41}{space 1}   -0.79{col 50}{space 3}0.432{col 58}{space 4}-.0629997{col 71}{space 3} .0269987
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0242173{col 30}{space 2} .0227597{col 41}{space 1}    1.06{col 50}{space 3}0.288{col 58}{space 4}-.0204808{col 71}{space 3} .0689154
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0031152{col 30}{space 2}  .008456{col 41}{space 1}   -0.37{col 50}{space 3}0.713{col 58}{space 4}-.0197221{col 71}{space 3} .0134916
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0021395{col 30}{space 2} .0278837{col 41}{space 1}    0.08{col 50}{space 3}0.939{col 58}{space 4}-.0526217{col 71}{space 3} .0569007
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0015656{col 30}{space 2}  .012246{col 41}{space 1}   -0.13{col 50}{space 3}0.898{col 58}{space 4}-.0256156{col 71}{space 3} .0224844
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.020933{col 30}{space 2} .0213746{col 41}{space 1}   -0.98{col 50}{space 3}0.328{col 58}{space 4}-.0629108{col 71}{space 3} .0210448
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0325893{col 30}{space 2} .0788506{col 41}{space 1}    0.41{col 50}{space 3}0.680{col 58}{space 4}-.1222664{col 71}{space 3} .1874451
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,579
                                                {txt}F(10, 602)        =  {res}     9.99
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0082
                                                {txt}Root MSE          =    {res} .27469

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  fgot_above_ext{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.029925{col 30}{space 2} .0170751{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.0634591{col 71}{space 3}  .003609
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0024561{col 30}{space 2} .0228479{col 41}{space 1}    0.11{col 50}{space 3}0.914{col 58}{space 4}-.0424151{col 71}{space 3} .0473273
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}   -.0587{col 30}{space 2} .0185651{col 41}{space 1}   -3.16{col 50}{space 3}0.002{col 58}{space 4}-.0951602{col 71}{space 3}-.0222398
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0132363{col 30}{space 2} .0315485{col 41}{space 1}   -0.42{col 50}{space 3}0.675{col 58}{space 4}-.0751949{col 71}{space 3} .0487222
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0015118{col 30}{space 2} .0103781{col 41}{space 1}   -0.15{col 50}{space 3}0.884{col 58}{space 4}-.0218936{col 71}{space 3} .0188699
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0015266{col 30}{space 2} .0185875{col 41}{space 1}    0.08{col 50}{space 3}0.935{col 58}{space 4}-.0349777{col 71}{space 3} .0380308
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0059735{col 30}{space 2} .0037083{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0013092{col 71}{space 3} .0132563
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0276405{col 30}{space 2} .0111274{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0057873{col 71}{space 3} .0494937
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0845469{col 30}{space 2} .0117673{col 41}{space 1}   -7.18{col 50}{space 3}0.000{col 58}{space 4}-.1076568{col 71}{space 3}-.0614369
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0028106{col 30}{space 2}  .019623{col 41}{space 1}   -0.14{col 50}{space 3}0.886{col 58}{space 4}-.0413484{col 71}{space 3} .0357272
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0391795{col 30}{space 2} .0245244{col 41}{space 1}    1.60{col 50}{space 3}0.111{col 58}{space 4}-.0089843{col 71}{space 3} .0873432
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,579}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:603}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(9, 602)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.4101}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0364}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2698}

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  fgot_above_ext{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0203637{col 30}{space 2} .0427888{col 41}{space 1}   -0.48{col 50}{space 3}0.634{col 58}{space 4}-.1043972{col 71}{space 3} .0636698
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0330347{col 30}{space 2} .0799843{col 41}{space 1}   -0.41{col 50}{space 3}0.680{col 58}{space 4}-.1901168{col 71}{space 3} .1240475
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0451519{col 30}{space 2} .0852442{col 41}{space 1}    0.53{col 50}{space 3}0.597{col 58}{space 4}-.1222604{col 71}{space 3} .2125641
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.2038671{col 30}{space 2} .1377538{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.4744035{col 71}{space 3} .0666693
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0308502{col 30}{space 2} .0521908{col 41}{space 1}    0.59{col 50}{space 3}0.555{col 58}{space 4}-.0716481{col 71}{space 3} .1333484
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0176973{col 30}{space 2}  .078087{col 41}{space 1}   -0.23{col 50}{space 3}0.821{col 58}{space 4}-.1710533{col 71}{space 3} .1356587
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0017911{col 30}{space 2} .0091551{col 41}{space 1}    0.20{col 50}{space 3}0.845{col 58}{space 4}-.0161887{col 71}{space 3} .0197708
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0089476{col 30}{space 2} .0369153{col 41}{space 1}   -0.24{col 50}{space 3}0.809{col 58}{space 4}-.0814461{col 71}{space 3} .0635509
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.1253775{col 30}{space 2} .0632074{col 41}{space 1}   -1.98{col 50}{space 3}0.048{col 58}{space 4}-.2495112{col 71}{space 3}-.0012437
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0204324{col 30}{space 2} .0448241{col 41}{space 1}    0.46{col 50}{space 3}0.649{col 58}{space 4}-.0675982{col 71}{space 3} .1084631
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1387946{col 30}{space 2} .0837891{col 41}{space 1}    1.66{col 50}{space 3}0.098{col 58}{space 4}-.0257599{col 71}{space 3} .3033491
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,579
                                                {txt}F(10, 602)        =  {res}     2.40
                                                {txt}Prob > F          = {res}    0.0084
                                                {txt}R-squared         = {res}    0.0046
                                                {txt}Root MSE          =    {res} .13668

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fruns_any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0094786{col 30}{space 2} .0084857{col 41}{space 1}   -1.12{col 50}{space 3}0.264{col 58}{space 4}-.0261438{col 71}{space 3} .0071865
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0157658{col 30}{space 2} .0134815{col 41}{space 1}    1.17{col 50}{space 3}0.243{col 58}{space 4}-.0107108{col 71}{space 3} .0422424
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0271453{col 30}{space 2} .0109831{col 41}{space 1}   -2.47{col 50}{space 3}0.014{col 58}{space 4}-.0487152{col 71}{space 3}-.0055753
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0089202{col 30}{space 2} .0164675{col 41}{space 1}    0.54{col 50}{space 3}0.588{col 58}{space 4}-.0234205{col 71}{space 3} .0412608
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0049271{col 30}{space 2} .0053937{col 41}{space 1}   -0.91{col 50}{space 3}0.361{col 58}{space 4}-.0155198{col 71}{space 3} .0056656
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0060573{col 30}{space 2} .0121013{col 41}{space 1}    0.50{col 50}{space 3}0.617{col 58}{space 4}-.0177085{col 71}{space 3} .0298231
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0029576{col 30}{space 2} .0017192{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4} -.006334{col 71}{space 3} .0004187
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0013572{col 30}{space 2} .0040344{col 41}{space 1}   -0.34{col 50}{space 3}0.737{col 58}{space 4}-.0092804{col 71}{space 3}  .006566
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0229204{col 30}{space 2} .0065224{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.0357299{col 71}{space 3}-.0101109
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0038533{col 30}{space 2} .0112019{col 41}{space 1}    0.34{col 50}{space 3}0.731{col 58}{space 4}-.0181462{col 71}{space 3} .0258528
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0311751{col 30}{space 2} .0099503{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0116336{col 71}{space 3} .0507166
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 52}{lalign 17:Number of obs}{col 69} = {res}{ralign 7:1,579}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 52}{lalign 17:No. of categories}{col 69} = {res}{ralign 7:603}
{txt}{col 52}{lalign 17:{help j_robustsingular##|_new:F(9, 602)}}{col 69} = {res}{ralign 7:.}
{txt}{col 52}{lalign 17:Prob > F}{col 69} = {res}{ralign 7:.}
{txt}{col 52}{lalign 17:R-squared}{col 69} = {res}{ralign 7:0.3405}
{txt}{col 52}{lalign 17:Adj R-squared}{col 69} = {res}{ralign 7:-0.0774}
{txt}{col 52}{lalign 17:Root MSE}{col 69} = {res}{ralign 7:0.1417}

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}       fruns_any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0146012{col 30}{space 2} .0230451{col 41}{space 1}   -0.63{col 50}{space 3}0.527{col 58}{space 4}-.0598599{col 71}{space 3} .0306574
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0008896{col 30}{space 2} .0310856{col 41}{space 1}    0.03{col 50}{space 3}0.977{col 58}{space 4}-.0601597{col 71}{space 3} .0619389
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0852719{col 30}{space 2} .0722092{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0565406{col 71}{space 3} .2270843
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0433112{col 30}{space 2} .0682139{col 41}{space 1}    0.63{col 50}{space 3}0.526{col 58}{space 4}-.0906549{col 71}{space 3} .1772773
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0069034{col 30}{space 2} .0207152{col 41}{space 1}    0.33{col 50}{space 3}0.739{col 58}{space 4}-.0337795{col 71}{space 3} .0475863
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0653115{col 30}{space 2} .0536718{col 41}{space 1}    1.22{col 50}{space 3}0.224{col 58}{space 4}-.0400953{col 71}{space 3} .1707183
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0060456{col 30}{space 2}  .003862{col 41}{space 1}   -1.57{col 50}{space 3}0.118{col 58}{space 4}-.0136302{col 71}{space 3} .0015389
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}-.0240408{col 30}{space 2} .0163444{col 41}{space 1}   -1.47{col 50}{space 3}0.142{col 58}{space 4}-.0561398{col 71}{space 3} .0080582
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0166953{col 30}{space 2} .0209605{col 41}{space 1}   -0.80{col 50}{space 3}0.426{col 58}{space 4}-.0578599{col 71}{space 3} .0244692
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0470671{col 30}{space 2} .0254915{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4}-.0029961{col 71}{space 3} .0971302
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0388108{col 30}{space 2} .0419348{col 41}{space 1}    0.93{col 50}{space 3}0.355{col 58}{space 4}-.0435454{col 71}{space 3} .1211671
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         
. 
.         *Continue table
.         tex Electoral victory & `nfb1_total_cont_num_d' &  `fb1_total_cont_num_d'& `nfb1_contract' & `fb1_contract' & `fb1_got_above_ext' & `fb1_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \  p-value & `nfp_v_total_cont_num_d' &  `fp_v_total_cont_num_d' & `nfp_v_contract' & `fp_v_contract' & `fp_v_got_above_ext' & `fp_v_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_total_cont_num_d',`nfuci_total_cont_num_d'] & [`flci_total_cont_num_d',`fuci_total_cont_num_d'] &  [`nflci_contract',`nfuci_contract'] & [`flci_contract',`fuci_contract'] & [`flci_got_above_ext',`fuci_got_above_ext'] & [`flci_runs_any',`fuci_runs_any']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}. 
.         tex Electoral victory (FE) & `nfb1f_total_cont_num_d' &  `fb1f_total_cont_num_d'& `nfb1f_contract' & `fb1f_contract' & `fb1f_got_above_ext' & `fb1f_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \  p-value & `nfp_vf_total_cont_num_d' &  `fp_vf_total_cont_num_d' & `nfp_vf_contract' & `fp_vf_contract' & `fp_vf_got_above_ext' & `fp_vf_runs_any' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflcif_total_cont_num_d',`nfucif_total_cont_num_d'] & [`flcif_total_cont_num_d',`fucif_total_cont_num_d'] &  [`nflcif_contract',`nfucif_contract'] & [`flcif_contract',`fucif_contract'] & [`flcif_got_above_ext',`fucif_got_above_ext'] & [`flcif_runs_any',`fucif_runs_any']\\
{res}{txt}
{com}.         tex & & & \\    
{res}{txt}
{com}.         
.         
.         tex Observations &`nfN_total_cont_num_d' &  `fN_total_cont_num_d' & `nfN_contract'& `fN_contract' & `fN_got_above_ext' & `fN_runs_any' \\
{res}{txt}
{com}.         tex Mean & `nfmean_total_cont_num_d' &`fmean_total_cont_num_d'  &  `nfmean_contract' & `fmean_contract' & `fmean_got_above_ext' & `fmean_runs_any' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on benefits received by the donor. Sample includes donors to the winner and third-placed candidates. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, and non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all family and non-family donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.     tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableG10.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\donor_level_persist_rep.dta",clear
{txt}
{com}. *New donor-level family (f) and (nf) variable generation
. 
. keep if rank==1|rank==2|rank==3
{txt}(0 observations deleted)

{com}. drop if rank==.
{txt}(0 observations deleted)

{com}. replace b5=. if b2!=0
{txt}(270 real changes made, 270 to missing)

{com}. 
. gen treat=0
{txt}
{com}. replace treat=1 if rank==1
{txt}(4,263 real changes made)

{com}. 
. gen nfdonate_15any = donate_15any if family==0
{txt}(2,365 missing values generated)

{com}. gen fdonate_15any = donate_15any if family==1
{txt}(6,166 missing values generated)

{com}. gen nfb5 = b5 if family==0
{txt}(2,588 missing values generated)

{com}. gen fb5 = b5 if family==1
{txt}(6,213 missing values generated)

{com}. 
. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableG10.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableG10.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableG10.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations comparison with third-placed candidate (candidate's family members vs. Non members){c )-}\label{c -(}tab:donation_fam_nofam_l_ols1_3{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c {c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Mayor  \\ 
{res}{txt}
{com}.         tex & (1) & (2)  \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}\\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach var in donate_15any b5{c -(}
{txt}  2{com}.                 
.                 quietly: regress f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  3{com}.                 quietly sum f`var' if e(sample)
{txt}  4{com}.                         local fmean_`var' : di %5.3f r(mean)
{txt}  5{com}.                         local fsd_`var' : di %5.3f r(sd)                
{txt}  6{com}.                 
.                 regress f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt}  7{com}. 
.                 local fN_`var' : di %5.0f e(N)
{txt}  8{com}.                 local fR2_`var' : di %5.3f e(r2)
{txt}  9{com}. 
.                 matrix b = e(b)
{txt} 10{com}.                 matrix v = e(V)
{txt} 11{com}.                 matrix res=r(table)
{txt} 12{com}.                 
.                 local fb1_`var' : di %5.3f b[1,1]
{txt} 13{com}.                 local fse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 14{com}.                 local fp_v_`var' :di %5.3f res[4,1]
{txt} 15{com}.                 local fuci_`var': di %5.3f res[6,1]
{txt} 16{com}.                 local flci_`var': di %5.3f res[5,1]
{txt} 17{com}. 
. 
.                 areg f`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample),absorb(muni_code) vce(cluster muni_code)
{txt} 18{com}. 
. 
.                 matrix bf = e(b)
{txt} 19{com}.                 matrix vf = e(V)
{txt} 20{com}.                 matrix resf=r(table)
{txt} 21{com}.                 
.                 local fb1f_`var' : di %5.3f bf[1,1]
{txt} 22{com}.                 local fse1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 23{com}.                 local fp_vf_`var' :di %5.3f resf[4,1]
{txt} 24{com}.                 local fucif_`var': di %5.3f resf[6,1]
{txt} 25{com}.                 local flcif_`var': di %5.3f resf[5,1]
{txt} 26{com}.                 
.                 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                         quietly: regress nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt} 27{com}.                         quietly sum nf`var' if e(sample)
{txt} 28{com}.                         local nfmean_`var' : di %5.3f r(mean)
{txt} 29{com}.                         local nfsd_`var' : di %5.3f r(sd)               
{txt} 30{com}.                 
.                 regress nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if (rank==1|rank==3), vce(cluster muni_code)
{txt} 31{com}. 
.                 local nfN_`var' : di %5.0f e(N)
{txt} 32{com}.                 local nfR2_`var' : di %5.3f e(r2)
{txt} 33{com}. 
.                 matrix b = e(b)
{txt} 34{com}.                 matrix v = e(V)
{txt} 35{com}.                 matrix res=r(table)
{txt} 36{com}.                 
.                 local nfb1_`var' : di %5.3f b[1,1]
{txt} 37{com}.                 local nfse1_`var' : di %5.3f sqrt(v[1,1])
{txt} 38{com}.                 local nfp_v_`var' :di %5.3f res[4,1]
{txt} 39{com}.                 local nfuci_`var': di %5.3f res[6,1]
{txt} 40{com}.                 local nflci_`var': di %5.3f res[5,1]
{txt} 41{com}.         
.         
.         areg nf`var' treat sanc_before ilegal p_prop elec_exp pol_exp_d  rank_don_alt_all lcont_donor_all contraloria above_lim if e(sample), absorb(muni_code) vce(cluster muni_code)
{txt} 42{com}.         
.         matrix bf = e(b)
{txt} 43{com}.                 matrix vf = e(V)
{txt} 44{com}.                 matrix resf=r(table)
{txt} 45{com}.                 
.                 local nfb1f_`var' : di %5.3f bf[1,1]
{txt} 46{com}.                 local nfse1f_`var' : di %5.3f sqrt(vf[1,1])
{txt} 47{com}.                 local nfp_vf_`var' :di %5.3f resf[4,1]
{txt} 48{com}.                 local nfucif_`var': di %5.3f resf[6,1]
{txt} 49{com}.                 local nflcif_`var': di %5.3f resf[5,1]
{txt} 50{com}.         
.         
.         {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,579
                                                {txt}F(10, 602)        =  {res}     3.79
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0226
                                                {txt}Root MSE          =    {res} .21628

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   fdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0610228{col 30}{space 2} .0175019{col 41}{space 1}   -3.49{col 50}{space 3}0.001{col 58}{space 4} -.095395{col 71}{space 3}-.0266505
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0203095{col 30}{space 2} .0281551{col 41}{space 1}    0.72{col 50}{space 3}0.471{col 58}{space 4}-.0349847{col 71}{space 3} .0756037
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}-.0208327{col 30}{space 2} .0186103{col 41}{space 1}   -1.12{col 50}{space 3}0.263{col 58}{space 4}-.0573817{col 71}{space 3} .0157164
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .0382178{col 30}{space 2} .0305326{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.0217455{col 71}{space 3} .0981811
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0045205{col 30}{space 2} .0078116{col 41}{space 1}   -0.58{col 50}{space 3}0.563{col 58}{space 4}-.0198617{col 71}{space 3} .0108207
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0059826{col 30}{space 2} .0172253{col 41}{space 1}   -0.35{col 50}{space 3}0.728{col 58}{space 4}-.0398116{col 71}{space 3} .0278463
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0053774{col 30}{space 2} .0050873{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0046137{col 71}{space 3} .0153684
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0164605{col 30}{space 2} .0082249{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0003075{col 71}{space 3} .0326134
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0477379{col 30}{space 2} .0111151{col 41}{space 1}   -4.29{col 50}{space 3}0.000{col 58}{space 4} -.069567{col 71}{space 3}-.0259087
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} .0032245{col 30}{space 2} .0167819{col 41}{space 1}    0.19{col 50}{space 3}0.848{col 58}{space 4}-.0297337{col 71}{space 3} .0361827
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0429991{col 30}{space 2} .0212126{col 41}{space 1}    2.03{col 50}{space 3}0.043{col 58}{space 4} .0013393{col 71}{space 3} .0846589
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,579}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:603}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(9, 602)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.4223}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0563}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2117}

{txt}{ralign 82:(Std. err. adjusted for {res:603} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   fdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} -.071407{col 30}{space 2} .0410426{col 41}{space 1}   -1.74{col 50}{space 3}0.082{col 58}{space 4}-.1520111{col 71}{space 3}  .009197
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0134532{col 30}{space 2} .0593667{col 41}{space 1}    0.23{col 50}{space 3}0.821{col 58}{space 4}-.1031377{col 71}{space 3} .1300442
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .1712556{col 30}{space 2} .1234424{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0711746{col 71}{space 3} .4136858
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .1189511{col 30}{space 2} .1047332{col 41}{space 1}    1.14{col 50}{space 3}0.257{col 58}{space 4}-.0867358{col 71}{space 3}  .324638
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0148318{col 30}{space 2} .0432637{col 41}{space 1}   -0.34{col 50}{space 3}0.732{col 58}{space 4}-.0997979{col 71}{space 3} .0701344
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0320341{col 30}{space 2} .0680033{col 41}{space 1}    0.47{col 50}{space 3}0.638{col 58}{space 4}-.1015185{col 71}{space 3} .1655867
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0028423{col 30}{space 2} .0115039{col 41}{space 1}    0.25{col 50}{space 3}0.805{col 58}{space 4}-.0197503{col 71}{space 3}  .025435
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0469729{col 30}{space 2} .0387207{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4}-.0290711{col 71}{space 3} .1230169
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0023411{col 30}{space 2} .0259366{col 41}{space 1}   -0.09{col 50}{space 3}0.928{col 58}{space 4}-.0532784{col 71}{space 3} .0485961
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0037327{col 30}{space 2} .0372997{col 41}{space 1}   -0.10{col 50}{space 3}0.920{col 58}{space 4}-.0769861{col 71}{space 3} .0695207
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0267181{col 30}{space 2} .0926731{col 41}{space 1}   -0.29{col 50}{space 3}0.773{col 58}{space 4}-.2087199{col 71}{space 3} .1552837
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     4,199
                                                {txt}{help j_robustsingular:F(9, 610) }        =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0229
                                                {txt}Root MSE          =    {res} .27851

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  nfdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0060797{col 30}{space 2} .0145969{col 41}{space 1}   -0.42{col 50}{space 3}0.677{col 58}{space 4} -.034746{col 71}{space 3} .0225865
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0151793{col 30}{space 2} .0276359{col 41}{space 1}    0.55{col 50}{space 3}0.583{col 58}{space 4}-.0390937{col 71}{space 3} .0694524
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}  .933893{col 30}{space 2} .0180177{col 41}{space 1}   51.83{col 50}{space 3}0.000{col 58}{space 4} .8985087{col 71}{space 3} .9692774
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}-.0135755{col 30}{space 2} .0320119{col 41}{space 1}   -0.42{col 50}{space 3}0.672{col 58}{space 4}-.0764424{col 71}{space 3} .0492913
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0056578{col 30}{space 2} .0060703{col 41}{space 1}   -0.93{col 50}{space 3}0.352{col 58}{space 4}-.0175791{col 71}{space 3} .0062634
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0068584{col 30}{space 2} .0164017{col 41}{space 1}    0.42{col 50}{space 3}0.676{col 58}{space 4}-.0253523{col 71}{space 3} .0390691
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0019039{col 30}{space 2} .0009687{col 41}{space 1}    1.97{col 50}{space 3}0.050{col 58}{space 4} 1.55e-06{col 71}{space 3} .0038063
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2}  .047646{col 30}{space 2}  .009163{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .0296513{col 71}{space 3} .0656408
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} -.032523{col 30}{space 2} .0465069{col 41}{space 1}   -0.70{col 50}{space 3}0.485{col 58}{space 4}-.1238562{col 71}{space 3} .0588101
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0223752{col 30}{space 2} .0274431{col 41}{space 1}   -0.82{col 50}{space 3}0.415{col 58}{space 4}-.0762696{col 71}{space 3} .0315192
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0198952{col 30}{space 2} .0280092{col 41}{space 1}    0.71{col 50}{space 3}0.478{col 58}{space 4}-.0351109{col 71}{space 3} .0749014
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,199}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:611}
{txt}{col 53}{lalign 17:F({res:9}, {res:610})}{col 70} = {res}{ralign 6:2.13}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0255}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2228}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0884}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2687}

{txt}{ralign 82:(Std. err. adjusted for {res:611} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}  nfdonate_15any{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2} .0069216{col 30}{space 2} .0226196{col 41}{space 1}    0.31{col 50}{space 3}0.760{col 58}{space 4}-.0375002{col 71}{space 3} .0513434
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0108865{col 30}{space 2} .0388243{col 41}{space 1}   -0.28{col 50}{space 3}0.779{col 58}{space 4} -.087132{col 71}{space 3}  .065359
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2} .0034445{col 30}{space 2} .0676015{col 41}{space 1}    0.05{col 50}{space 3}0.959{col 58}{space 4}-.1293155{col 71}{space 3} .1362045
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0208564{col 30}{space 2}  .015682{col 41}{space 1}    1.33{col 50}{space 3}0.184{col 58}{space 4}-.0099408{col 71}{space 3} .0516536
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0717688{col 30}{space 2} .0382133{col 41}{space 1}   -1.88{col 50}{space 3}0.061{col 58}{space 4}-.1468145{col 71}{space 3} .0032769
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}-.0073206{col 30}{space 2} .0034008{col 41}{space 1}   -2.15{col 50}{space 3}0.032{col 58}{space 4}-.0139992{col 71}{space 3} -.000642
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0065965{col 30}{space 2} .0160357{col 41}{space 1}    0.41{col 50}{space 3}0.681{col 58}{space 4}-.0248953{col 71}{space 3} .0380883
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} -.050427{col 30}{space 2} .0331904{col 41}{space 1}   -1.52{col 50}{space 3}0.129{col 58}{space 4}-.1156083{col 71}{space 3} .0147543
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.022547{col 30}{space 2} .0328518{col 41}{space 1}   -0.69{col 50}{space 3}0.493{col 58}{space 4}-.0870633{col 71}{space 3} .0419693
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1356261{col 30}{space 2} .0482514{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4}  .040867{col 71}{space 3} .2303852
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                               Number of obs     = {res}     1,548
                                                {txt}F(10, 599)        =  {res}     2.71
                                                {txt}Prob > F          = {res}    0.0029
                                                {txt}R-squared         = {res}    0.0308
                                                {txt}Root MSE          =    {res} .17126

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}             fb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0541582{col 30}{space 2} .0164701{col 41}{space 1}   -3.29{col 50}{space 3}0.001{col 58}{space 4}-.0865042{col 71}{space 3}-.0218121
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0060401{col 30}{space 2} .0138184{col 41}{space 1}   -0.44{col 50}{space 3}0.662{col 58}{space 4}-.0331785{col 71}{space 3} .0210983
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0048093{col 30}{space 2} .0118238{col 41}{space 1}    0.41{col 50}{space 3}0.684{col 58}{space 4}-.0184118{col 71}{space 3} .0280304
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2}  .051132{col 30}{space 2} .0236668{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4}  .004652{col 71}{space 3}  .097612
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0083411{col 30}{space 2} .0062023{col 41}{space 1}   -1.34{col 50}{space 3}0.179{col 58}{space 4} -.020522{col 71}{space 3} .0038398
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0064774{col 30}{space 2} .0158712{col 41}{space 1}   -0.41{col 50}{space 3}0.683{col 58}{space 4}-.0376474{col 71}{space 3} .0246926
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0026842{col 30}{space 2} .0037555{col 41}{space 1}    0.71{col 50}{space 3}0.475{col 58}{space 4}-.0046913{col 71}{space 3} .0100598
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0127007{col 30}{space 2} .0070455{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0011362{col 71}{space 3} .0265375
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0293332{col 30}{space 2} .0093458{col 41}{space 1}   -3.14{col 50}{space 3}0.002{col 58}{space 4}-.0476876{col 71}{space 3}-.0109787
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0003185{col 30}{space 2} .0135731{col 41}{space 1}   -0.02{col 50}{space 3}0.981{col 58}{space 4}-.0269751{col 71}{space 3} .0263381
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0359913{col 30}{space 2} .0188124{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4} -.000955{col 71}{space 3} .0729375
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:1,548}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:600}
{txt}{col 53}{lalign 17:{help j_robustsingular##|_new:F(9, 599)}}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:.}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.4811}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.1443}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.1603}

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}             fb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0480621{col 30}{space 2} .0399019{col 41}{space 1}   -1.20{col 50}{space 3}0.229{col 58}{space 4}-.1264268{col 71}{space 3} .0303025
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0027145{col 30}{space 2} .0564988{col 41}{space 1}    0.05{col 50}{space 3}0.962{col 58}{space 4}-.1082453{col 71}{space 3} .1136742
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2} .0822583{col 30}{space 2} .1214623{col 41}{space 1}    0.68{col 50}{space 3}0.499{col 58}{space 4}-.1562855{col 71}{space 3} .3208021
{txt}{space 10}p_prop {c |}{col 18}{res}{space 2} .1000551{col 30}{space 2} .1023845{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.1010211{col 71}{space 3} .3011313
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2} .0097553{col 30}{space 2} .0285879{col 41}{space 1}    0.34{col 50}{space 3}0.733{col 58}{space 4}-.0463893{col 71}{space 3} .0658999
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2}-.0294622{col 30}{space 2} .0522307{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4}-.1320396{col 71}{space 3} .0731153
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2}  .000557{col 30}{space 2}  .010117{col 41}{space 1}    0.06{col 50}{space 3}0.956{col 58}{space 4}-.0193121{col 71}{space 3} .0204261
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0360272{col 30}{space 2} .0352076{col 41}{space 1}    1.02{col 50}{space 3}0.307{col 58}{space 4}-.0331182{col 71}{space 3} .1051727
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2} .0006235{col 30}{space 2} .0191221{col 41}{space 1}    0.03{col 50}{space 3}0.974{col 58}{space 4} -.036931{col 71}{space 3} .0381779
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2} -.011975{col 30}{space 2} .0286568{col 41}{space 1}   -0.42{col 50}{space 3}0.676{col 58}{space 4} -.068255{col 71}{space 3} .0443049
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0159968{col 30}{space 2} .0881935{col 41}{space 1}   -0.18{col 50}{space 3}0.856{col 58}{space 4}-.1892028{col 71}{space 3} .1572093
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res}     4,055
                                                {txt}F(9, 599)         =  {res}     6.51
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0321
                                                {txt}Root MSE          =    {res} .22313

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            nfb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0098806{col 30}{space 2} .0131991{col 41}{space 1}   -0.75{col 50}{space 3}0.454{col 58}{space 4}-.0358028{col 71}{space 3} .0160415
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2} .0010722{col 30}{space 2} .0228084{col 41}{space 1}    0.05{col 50}{space 3}0.963{col 58}{space 4} -.043722{col 71}{space 3} .0458664
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0005029{col 30}{space 2} .0281957{col 41}{space 1}   -0.02{col 50}{space 3}0.986{col 58}{space 4}-.0558773{col 71}{space 3} .0548716
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}-.0104581{col 30}{space 2} .0057212{col 41}{space 1}   -1.83{col 50}{space 3}0.068{col 58}{space 4}-.0216941{col 71}{space 3} .0007779
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} .0167696{col 30}{space 2} .0133767{col 41}{space 1}    1.25{col 50}{space 3}0.210{col 58}{space 4}-.0095012{col 71}{space 3} .0430405
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} .0019077{col 30}{space 2} .0006678{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0005962{col 71}{space 3} .0032193
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0484145{col 30}{space 2} .0083924{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .0319325{col 71}{space 3} .0648965
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0000518{col 30}{space 2} .0463961{col 41}{space 1}   -0.00{col 50}{space 3}0.999{col 58}{space 4}-.0911706{col 71}{space 3}  .091067
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0261234{col 30}{space 2} .0251882{col 41}{space 1}   -1.04{col 50}{space 3}0.300{col 58}{space 4}-.0755914{col 71}{space 3} .0233447
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0180642{col 30}{space 2} .0234605{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}-.0641389{col 71}{space 3} .0280106
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 6 2}note: {bf:ilegal} omitted because of collinearity.{p_end}
{res}
{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 17:Number of obs}{col 70} = {res}{ralign 6:4,055}
{txt}{col 1}Absorbed variable: {res:muni_code}{col 53}{lalign 17:No. of categories}{col 70} = {res}{ralign 6:600}
{txt}{col 53}{lalign 17:F({res:9}, {res:599})}{col 70} = {res}{ralign 6:2.60}
{txt}{col 53}{lalign 17:Prob > F}{col 70} = {res}{ralign 6:0.0060}
{txt}{col 53}{lalign 17:R-squared}{col 70} = {res}{ralign 6:0.2322}
{txt}{col 53}{lalign 17:Adj R-squared}{col 70} = {res}{ralign 6:0.0967}
{txt}{col 53}{lalign 17:Root MSE}{col 70} = {res}{ralign 6:0.2153}

{txt}{ralign 82:(Std. err. adjusted for {res:600} clusters in {res:muni_code})}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            nfb5{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}treat {c |}{col 18}{res}{space 2}-.0139505{col 30}{space 2} .0188614{col 41}{space 1}   -0.74{col 50}{space 3}0.460{col 58}{space 4} -.050993{col 71}{space 3} .0230919
{txt}{space 5}sanc_before {c |}{col 18}{res}{space 2}-.0269483{col 30}{space 2} .0366012{col 41}{space 1}   -0.74{col 50}{space 3}0.462{col 58}{space 4}-.0988305{col 71}{space 3} .0449339
{txt}{space 10}ilegal {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 10}p_prop {c |}{col 18}{res}{space 2}-.0050531{col 30}{space 2}  .068589{col 41}{space 1}   -0.07{col 50}{space 3}0.941{col 58}{space 4}-.1397573{col 71}{space 3} .1296512
{txt}{space 8}elec_exp {c |}{col 18}{res}{space 2}  .022188{col 30}{space 2} .0167538{col 41}{space 1}    1.32{col 50}{space 3}0.186{col 58}{space 4}-.0107154{col 71}{space 3} .0550914
{txt}{space 7}pol_exp_d {c |}{col 18}{res}{space 2} -.046519{col 30}{space 2} .0352125{col 41}{space 1}   -1.32{col 50}{space 3}0.187{col 58}{space 4} -.115674{col 71}{space 3}  .022636
{txt}rank_don_alt_all {c |}{col 18}{res}{space 2} -.005681{col 30}{space 2} .0031318{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4}-.0118317{col 71}{space 3} .0004696
{txt}{space 1}lcont_donor_all {c |}{col 18}{res}{space 2} .0187437{col 30}{space 2} .0137497{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0082597{col 71}{space 3} .0457472
{txt}{space 5}contraloria {c |}{col 18}{res}{space 2}-.0312653{col 30}{space 2} .0321969{col 41}{space 1}   -0.97{col 50}{space 3}0.332{col 58}{space 4}-.0944977{col 71}{space 3} .0319672
{txt}{space 7}above_lim {c |}{col 18}{res}{space 2}-.0390594{col 30}{space 2} .0307787{col 41}{space 1}   -1.27{col 50}{space 3}0.205{col 58}{space 4}-.0995067{col 71}{space 3} .0213879
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0879415{col 30}{space 2} .0432042{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0030913{col 71}{space 3} .1727917
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         *Continue table
.         tex Electoral victory & `fb1_donate_15any' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `fp_v_donate_15any' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_15any',`fuci_donate_15any'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & & \\
{res}{txt}
{com}. 
.         tex Electoral victory (FE) & `fb1f_donate_15any' & `fb1f_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `fp_vf_donate_15any' & `fp_vf_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flcif_donate_15any',`fucif_donate_15any'] & [`flcif_b5',`fucif_b5']  \\
{res}{txt}
{com}.         tex & & \\
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_15any' & `fN_b5' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_15any' & `fmean_b5' \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}. 
.                 tex Electoral victory & `nfb1_donate_15any' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `nfp_v_donate_15any' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_15any',`nfuci_donate_15any'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & &  \\
{res}{txt}
{com}.         
.         tex Electoral victory (FE) & `nfb1f_donate_15any' & `nfb1f_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `nfp_vf_donate_15any' & `nfp_vf_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflcif_donate_15any',`nfucif_donate_15any'] & [`nflcif_b5',`nfucif_b5']  \\
{res}{txt}
{com}.         tex & & \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_15any' & `nfN_b5' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_15any' & `nfmean_b5' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex \footnotesize{c -(}Ordinary least squares (OLS) estimates of the effect of donating to the winner on donating in the next election. Sample includes donors to the winner and third-placed candidates. All models include as controls: candidate's illegal registration of ID, being sanctioned by the Office of the Inspector General, elected posts, ran as candidate in past elections, and non-family donations as a fraction of campaign revenue, logged value of donation, donated above legal limit, sanctioned, rank of donation among all family and non-family donors. FE denote municipality fixed effects. Confidence intervals and p-values with clusters at the municipality level.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableH1.do"
{txt}
{com}. global dir "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"
{txt}
{com}. 
. 
. use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. 
. 
. gen treat=0
{txt}
{com}. replace treat=1 if rv2>0&rv2~=.
{txt}(981 real changes made)

{com}. 
. gen treat_rv2=treat*rv2
{txt}
{com}.         
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableH1.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableH1.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableH1.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (local councils){c )-}\label{c -(}tab:donations_council{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c{c )-} \hline
{res}{txt}
{com}.         tex Outcome:&  Any race  & Council & Runs again \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_any15 b5 runs_concejo{c -(}
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 quietly sum `x' if  rv2!=.
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' rv2 ,  p(1) vce(cluster muni_code)
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %5.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_bc)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 18{com}.                 scalar pval2_`x' = e(pv_rb)
{txt} 19{com}.                 
.                 
.                 regress `x' treat treat_rv2 rv2 , vce(cluster muni_code)
{txt} 20{com}. 
.                 local N_`x' : di %5.0f e(N)
{txt} 21{com}.                 local R2_`x' : di %5.3f e(r2)
{txt} 22{com}. 
.                 matrix b = e(b)
{txt} 23{com}.                 matrix v = e(V)
{txt} 24{com}.                 matrix res=r(table)
{txt} 25{com}.                 
.                 local b1_`x' : di %5.3f b[1,1]
{txt} 26{com}.                 local se1_`x' : di %5.3f sqrt(v[1,1])
{txt} 27{com}.                 local p_v_`x' :di %5.3f res[4,1]
{txt} 28{com}.                 local uci_`x': di %5.3f res[6,1]
{txt} 29{com}.                 local lci_`x': di %5.3f res[5,1]
{txt} 30{com}.                 
.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      469{col 34}      614{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.672{col 34}    5.672
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.644{col 34}   10.644
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04675{col 33} .03902{col 43}-1.1981{col 52}0.231{col 60}-.123225{col 73} .029725
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.2857{col 52}0.199{col 60}-.143267{col 73} .029764
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,757
                                                {txt}F(3, 606)         =  {res}     1.09
                                                {txt}Prob > F          = {res}    0.3534
                                                {txt}R-squared         = {res}    0.0018
                                                {txt}Root MSE          =    {res} .30462

{txt}{ralign 78:(Std. err. adjusted for {res:607} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}donate_any15{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2}-.0056778{col 26}{space 2}  .017919{col 37}{space 1}   -0.32{col 46}{space 3}0.751{col 54}{space 4}-.0408688{col 67}{space 3} .0295132
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0040048{col 26}{space 2} .0027173{col 37}{space 1}   -1.47{col 46}{space 3}0.141{col 54}{space 4}-.0093412{col 67}{space 3} .0013316
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2} .0030527{col 26}{space 2} .0018413{col 37}{space 1}    1.66{col 46}{space 3}0.098{col 54}{space 4}-.0005635{col 67}{space 3} .0066689
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1384132{col 26}{space 2} .0159123{col 37}{space 1}    8.70{col 46}{space 3}0.000{col 54}{space 4} .1071632{col 67}{space 3} .1696633
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      543{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    4.739{col 34}    4.739
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    8.715{col 34}    8.715
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      382{col 34}      442

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06746{col 33} .03738{col 43}-1.8046{col 52}0.071{col 60}-.140734{col 73} .005807
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.8704{col 52}0.061{col 60}-.161386{col 73} .003774
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,757
                                                {txt}F(3, 606)         =  {res}     2.82
                                                {txt}Prob > F          = {res}    0.0384
                                                {txt}R-squared         = {res}    0.0040
                                                {txt}Root MSE          =    {res}  .2477

{txt}{ralign 78:(Std. err. adjusted for {res:607} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}          b5{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2}-.0061123{col 26}{space 2} .0152247{col 37}{space 1}   -0.40{col 46}{space 3}0.688{col 54}{space 4}-.0360119{col 67}{space 3} .0237872
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0052894{col 26}{space 2}   .00198{col 37}{space 1}   -2.67{col 46}{space 3}0.008{col 54}{space 4} -.009178{col 67}{space 3}-.0014009
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2} .0033399{col 26}{space 2} .0012643{col 37}{space 1}    2.64{col 46}{space 3}0.008{col 54}{space 4}  .000857{col 67}{space 3} .0058228
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0988166{col 26}{space 2} .0132517{col 37}{space 1}    7.46{col 46}{space 3}0.000{col 54}{space 4} .0727917{col 67}{space 3} .1248415
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      543{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    4.737{col 34}    4.737
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    9.417{col 34}    9.417
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      448

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03203{col 33} .06285{col 43}0.5097{col 52}0.610{col 60}-.091151{col 73}  .15522
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}0.1699{col 52}0.865{col 60}-.126254{col 73} .150213
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,757
                                                {txt}F(3, 606)         =  {res}    26.20
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0476
                                                {txt}Root MSE          =    {res} .48456

{txt}{ralign 78:(Std. err. adjusted for {res:607} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}runs_concejo{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2} .2020979{col 26}{space 2} .0329153{col 37}{space 1}    6.14{col 46}{space 3}0.000{col 54}{space 4} .1374561{col 67}{space 3} .2667397
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0109158{col 26}{space 2} .0039449{col 37}{space 1}   -2.77{col 46}{space 3}0.006{col 54}{space 4}-.0186632{col 67}{space 3}-.0031684
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2} .0060734{col 26}{space 2} .0028118{col 37}{space 1}    2.16{col 46}{space 3}0.031{col 54}{space 4} .0005513{col 67}{space 3} .0115955
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4821977{col 26}{space 2} .0253592{col 37}{space 1}   19.01{col 46}{space 3}0.000{col 54}{space 4} .4323951{col 67}{space 3} .5320004
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Continue table
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}&\\
{res}{txt}
{com}. 
.         tex Electoral victory & `beta1_donate_any15' & `beta1_b5' & `beta1_runs_concejo' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `pval2_donate_any15' & `pval2_b5' & `pval2_runs_concejo' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`ser1_donate_any15',`ser2_donate_any15'] & [`ser1_b5',`ser2_b5'] & [`ser1_runs_concejo',`ser2_runs_concejo']\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}3{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}&\\
{res}{txt}
{com}. 
.     tex Electoral victory & `b1_donate_any15' & `b1_b5' & `b1_runs_concejo' \\
{res}{txt}
{com}.         tex \ \ \ \ p-value & `p_v_donate_any15' & `p_v_b5' & `p_v_runs_concejo' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`lci_donate_any15',`uci_donate_any15'] & [`lci_b5',`uci_b5'] & [`lci_runs_concejo',`uci_runs_concejo'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `N_donate_any15' & `N_b5' & `N_runs_concejo' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `Neff_donate_any15' & `Neff_b5' & `Neff_runs_concejo' \\
{res}{txt}
{com}.         tex Mean & `mean_donate_any15' & `mean_b5' & `mean_runs_concejo' \\
{res}{txt}
{com}.         *tex Effect Mean(\%) & `em1_donate_15any' & `em1_b5' & `em1_b2b' \\
.         tex Bandwidth & `bw_donate_any15' & `bw_b5' & `bw_runs_concejo' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(}
{res}{txt}
{com}.         tex Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. 95\% robust confidence intervals and robust p-values with clustering at the municipality level are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableH2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. 
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableH2.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableH2.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableH2.tex)
{res}{txt}
{com}.         
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Effect of donating to an election winner on future donations (candidate's family members vs. Non members, local councils){c )-}\label{c -(}tab:donation_fam_nofam_council{c )-}
{res}{txt}
{com}.         tex \centering
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c H{c )-} \hline
{res}{txt}
{com}.         tex Outcome : & Any race & Council & b2 \\ 
{res}{txt}
{com}.         tex & (1) & (2) & (3) \\ \hline
{res}{txt}
{com}.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Panel A: Candidates' family members{c )-}&\\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         *Model 1
.         foreach x in donate_any15 b5{c -(}
{txt}  2{com}.         
.                 
.                 use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}  3{com}.                 
.                 drop if fall==.
{txt}  4{com}.                 gen treat=0
{txt}  5{com}.                 replace treat=1 if rv2>0&rv2~=.
{txt}  6{com}.                 replace treat=. if rv2==.
{txt}  7{com}. 
.                 gen treat_rv2=treat*rv2
{txt}  8{com}.                                 
.                 *Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly sum f`x' 
{txt}  9{com}.                         local fmean_`x' : di %5.3f r(mean)
{txt} 10{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt} 11{com}.                         
.                 rdrobust f`x' rv2 ,  vce(cluster muni_code)
{txt} 12{com}. 
.                 *Local's for the table
.                 local fbw_`x' : di %5.2f `e(h_l)'
{txt} 13{com}.                 local fNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt} 14{com}.                 local fN_`x' = `e(N)'
{txt} 15{com}.                 local fbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 16{com}.                 local fbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 17{com}. 
.                 *Confidence intervals
.                         local fser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 18{com}.                         local fser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 19{com}.                         
. /* HERE*/       local fem1_`x' = (`fbeta1_`x''/`fmean_`x'')*100 
{txt} 20{com}.                         local fem1_`x' : di %5.2f `fem1_`x''
{txt} 21{com}.                         
.                 *P-values
.                 local fpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 22{com}.                 scalar fpval2_`x' = e(pv_rb)
{txt} 23{com}.                 
.                 
.                 regress f`x' treat treat_rv2 rv2, vce(cluster muni_code)
{txt} 24{com}. 
.                 local fN_`x' : di %5.0f e(N)
{txt} 25{com}.                 local fR2_`x' : di %5.3f e(r2)
{txt} 26{com}. 
.                 matrix b = e(b)
{txt} 27{com}.                 matrix v = e(V)
{txt} 28{com}.                 matrix res=r(table)
{txt} 29{com}.                 
.                 local fb1_`x' : di %5.3f b[1,1]
{txt} 30{com}.                 local fse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 31{com}.                 local fp_v_`x' :di %5.3f res[4,1]
{txt} 32{com}.                 local fuci_`x': di %5.3f res[6,1]
{txt} 33{com}.                 local flci_`x': di %5.3f res[5,1]
{txt} 34{com}.                 
.                 use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt} 35{com}.                 
.                 gen treat=0
{txt} 36{com}.                 replace treat=1 if rv2>0&rv2~=.
{txt} 37{com}.                 replace treat=. if rv2==.
{txt} 38{com}. 
.                 gen treat_rv2=treat*rv2
{txt} 39{com}.                 
.                 *No Family
.                 *Regressions
.                 *Summary statistics for the mean
.                 quietly sum nf`x' 
{txt} 40{com}.                         local nfmean_`x' : di %5.3f r(mean)
{txt} 41{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt} 42{com}. 
.                 rdrobust nf`x' rv2 ,  vce(cluster muni_code)
{txt} 43{com}. 
.                 *Local's for the table
.                 local nfbw_`x' : di %5.2f `e(h_l)'
{txt} 44{com}.                 local nfNeff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt} 45{com}.                 local nfN_`x' = `e(N)'
{txt} 46{com}.                 local nfbeta1_`x' : di %5.3f `e(tau_cl)'
{txt} 47{com}.                 local nfbeta2_`x' : di %5.3f `e(tau_bc)'
{txt} 48{com}. 
.                 *Confidence intervals
.                         local nfser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 49{com}.                         local nfser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 50{com}.                         
. /* HERE*/       local nfem1_`x' = (`nfbeta1_`x''/`nfmean_`x'')*100 
{txt} 51{com}.                         local nfem1_`x' : di %5.2f `nfem1_`x''
{txt} 52{com}.                         
.                 *P-values
.                 local nfpval2_`x' : di %5.3f `e(pv_rb)'
{txt} 53{com}.                 scalar nfpval2_`x' = e(pv_rb)
{txt} 54{com}.                 
.                 regress nf`x' treat treat_rv2 rv2 , vce(cluster muni_code)
{txt} 55{com}. 
.                 local nfN_`x' : di %5.0f e(N)
{txt} 56{com}.                 local nfR2_`x' : di %5.3f e(r2)
{txt} 57{com}. 
.                 matrix b = e(b)
{txt} 58{com}.                 matrix v = e(V)
{txt} 59{com}.                 matrix res=r(table)
{txt} 60{com}.                 
.                 local nfb1_`x' : di %5.3f b[1,1]
{txt} 61{com}.                 local nfse1_`x' : di %5.3f sqrt(v[1,1])
{txt} 62{com}.                 local nfp_v_`x' :di %5.3f res[4,1]
{txt} 63{com}.                 local nfuci_`x': di %5.3f res[6,1]
{txt} 64{com}.                 local nflci_`x': di %5.3f res[5,1]
{txt} 65{com}. 
.         {c )-}
{txt}(776 observations deleted)
(547 real changes made)
(0 real changes made)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      277{col 34}      362{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.131{col 34}    6.131
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    9.908{col 34}    9.908
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      259{col 34}      299

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02599{col 33} .04635{col 43}-0.5608{col 52}0.575{col 60}-.116834{col 73}  .06485
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.5914{col 52}0.554{col 60}-.137545{col 73} .073778
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       981
                                                {txt}F(3, 462)         =  {res}     1.90
                                                {txt}Prob > F          = {res}    0.1291
                                                {txt}R-squared         = {res}    0.0039
                                                {txt}Root MSE          =    {res} .27275

{txt}{ralign 78:(Std. err. adjusted for {res:463} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}fdonate_a~15{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2} .0092719{col 26}{space 2} .0260917{col 37}{space 1}    0.36{col 46}{space 3}0.722{col 54}{space 4}-.0420012{col 67}{space 3} .0605449
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0040727{col 26}{space 2} .0032843{col 37}{space 1}   -1.24{col 46}{space 3}0.216{col 54}{space 4}-.0105267{col 67}{space 3} .0023813
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2} .0033974{col 26}{space 2} .0021736{col 37}{space 1}    1.56{col 46}{space 3}0.119{col 54}{space 4} -.000874{col 67}{space 3} .0076687
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0996058{col 26}{space 2} .0179784{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} .0642763{col 67}{space 3} .1349353
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(981 real changes made)
(0 real changes made)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      313{col 34}      432{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.872{col 34}    7.872
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   14.322{col 34}   14.322
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      255{col 34}      304

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01958{col 33} .04802{col 43}-0.4077{col 52}0.683{col 60}-.113701{col 73}  .07454
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.3410{col 52}0.733{col 60}-.127276{col 73} .089552
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,007
                                                {txt}F(3, 383)         =  {res}     0.65
                                                {txt}Prob > F          = {res}    0.5829
                                                {txt}R-squared         = {res}    0.0023
                                                {txt}Root MSE          =    {res} .34197

{txt}{ralign 78:(Std. err. adjusted for {res:384} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}nfdonate_~15{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2}-.0117956{col 26}{space 2} .0235239{col 37}{space 1}   -0.50{col 46}{space 3}0.616{col 54}{space 4}-.0580478{col 67}{space 3} .0344566
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0052229{col 26}{space 2} .0038031{col 37}{space 1}   -1.37{col 46}{space 3}0.170{col 54}{space 4}-.0127006{col 67}{space 3} .0022548
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2} .0033094{col 26}{space 2} .0025392{col 37}{space 1}    1.30{col 46}{space 3}0.193{col 54}{space 4}-.0016832{col 67}{space 3}  .008302
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1760893{col 26}{space 2} .0244032{col 37}{space 1}    7.22{col 46}{space 3}0.000{col 54}{space 4} .1281082{col 67}{space 3} .2240703
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(776 observations deleted)
(547 real changes made)
(0 real changes made)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      344{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.585{col 34}    5.585
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    9.517{col 34}    9.517
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      255{col 34}      296

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03588{col 33} .04434{col 43}-0.8093{col 52}0.418{col 60}-.122792{col 73} .051023
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.9136{col 52}0.361{col 60}-.145297{col 73} .052909
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}       981
                                                {txt}F(3, 462)         =  {res}     1.41
                                                {txt}Prob > F          = {res}    0.2391
                                                {txt}R-squared         = {res}    0.0045
                                                {txt}Root MSE          =    {res} .25043

{txt}{ralign 78:(Std. err. adjusted for {res:463} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}         fb5{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2}   .03006{col 26}{space 2} .0222721{col 37}{space 1}    1.35{col 46}{space 3}0.178{col 54}{space 4}-.0137073{col 67}{space 3} .0738272
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2} -.004032{col 26}{space 2} .0030629{col 37}{space 1}   -1.32{col 46}{space 3}0.189{col 54}{space 4} -.010051{col 67}{space 3} .0019869
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2}  .001585{col 26}{space 2} .0020384{col 37}{space 1}    0.78{col 46}{space 3}0.437{col 54}{space 4}-.0024208{col 67}{space 3} .0055908
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0737717{col 26}{space 2} .0157464{col 37}{space 1}    4.69{col 46}{space 3}0.000{col 54}{space 4} .0428284{col 67}{space 3} .1047151
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}(981 real changes made)
(0 real changes made)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      260{col 34}      361{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.830{col 34}    5.830
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.601{col 34}   10.601
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      238{col 34}      284

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05351{col 33} .04754{col 43}-1.1258{col 52}0.260{col 60}-.146684{col 73} .039655
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.1979{col 52}0.231{col 60}-.169726{col 73} .040957
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

Linear regression                               Number of obs     = {res}     1,007
                                                {txt}F(3, 383)         =  {res}     3.51
                                                {txt}Prob > F          = {res}    0.0155
                                                {txt}R-squared         = {res}    0.0082
                                                {txt}Root MSE          =    {res} .26506

{txt}{ralign 78:(Std. err. adjusted for {res:384} clusters in {res:muni_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        nfb5{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}treat {c |}{col 14}{res}{space 2}-.0251835{col 26}{space 2} .0202462{col 37}{space 1}   -1.24{col 46}{space 3}0.214{col 54}{space 4}-.0649911{col 67}{space 3} .0146242
{txt}{space 3}treat_rv2 {c |}{col 14}{res}{space 2}-.0074482{col 26}{space 2} .0023624{col 37}{space 1}   -3.15{col 46}{space 3}0.002{col 54}{space 4} -.012093{col 67}{space 3}-.0028033
{txt}{space 9}rv2 {c |}{col 14}{res}{space 2}  .004645{col 26}{space 2} .0015173{col 37}{space 1}    3.06{col 46}{space 3}0.002{col 54}{space 4} .0016618{col 67}{space 3} .0076282
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1244689{col 26}{space 2} .0198409{col 37}{space 1}    6.27{col 46}{space 3}0.000{col 54}{space 4} .0854581{col 67}{space 3} .1634797
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. 
. 
.                 
. 
.         *Continue table
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `fbeta1_donate_any15' & `fbeta1_b5' & `fbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fpval2_donate_any15' & `fpval2_b5' & `fpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`fser1_donate_any15',`fser2_donate_any15'] & [`fser1_b5',`fser2_b5'] & [`fser1_b3',`fser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `fb1_donate_any15' & `fb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `fp_v_donate_any15' & `fp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`flci_donate_any15',`fuci_donate_any15'] & [`flci_b5',`fuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `fN_donate_any15' & `fN_b5' & `fN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `fNeff_donate_any15' & `fNeff_b5' & `fNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `fmean_donate_any15' & `fmean_b5' & `fmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `fbw_donate_any15' & `fbw_b5' & `fbw_b3' \\ 
{res}{txt}
{com}.         
.         tex & & & \\ \hline
{res}{txt}
{com}.         tex {c -(}Panel B: Non-family members{c )-}&  \\  
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}. 
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Local linear{c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfbeta1_donate_any15' & `nfbeta1_b5' & `nfbeta1_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfpval2_donate_any15' & `nfpval2_b5' & `nfpval2_b3' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nfser1_donate_any15',`nfser2_donate_any15'] & [`nfser1_b5',`nfser2_b5'] & [`nfser1_b3',`nfser2_b3'] \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}2{c )-}{c -(}l{c )-}{c -(}Parametric (linear){c )-}\\
{res}{txt}
{com}.         tex Electoral victory & `nfb1_donate_any15' & `nfb1_b5'  \\
{res}{txt}
{com}.         tex \ \ \ \ Robust p-value & `nfp_v_donate_any15' & `nfp_v_b5' \\
{res}{txt}
{com}.         tex \ \ \ \ CI 95\%  & [`nflci_donate_any15',`nfuci_donate_any15'] & [`nflci_b5',`nfuci_b5']  \\
{res}{txt}
{com}.         tex & & & \\
{res}{txt}
{com}.         
.         tex Observations & `nfN_donate_any15' & `nfN_b5' & `nfN_b3' \\
{res}{txt}
{com}.         tex Bandwidth obs. & `nfNeff_donate_any15' & `nfNeff_b5' & `nfNeff_b3' \\
{res}{txt}
{com}.         tex Mean & `nfmean_donate_any15' & `nfmean_b5' & `nfmean_b3' \\
{res}{txt}
{com}.         tex Bandwidth & `nfbw_donate_any15' & `nfbw_b5' & `nfbw_b3' \\ \hline
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \footnotesize{c -(} Local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth. Robust p-values with clustering at the municipality level and 95\% robust confidence intervals are computed following \cite{c -(}calonico_robust_2014{c )-}. Parametric linear model specification includes interaction of the treatment with the running variable and running variable. Bandwidth obs. denotes the number of observations in the optimal MSE bandwidth.
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close 
{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableH3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. global dir "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"
{txt}
{com}.                 
.                 use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
.         global balance_ind women sanc_before pol_exp_d elec_exp_d 
{txt}
{com}.         global balance_fin all total_income donations_total
{txt}
{com}.         global balance_donors family cont_donor_101 cont_donor_102 contraloria above_lim    
{txt}
{com}.         global balance_all $balance_ind $balance_fin $balance_donors
{txt}
{com}. 
. 
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableH3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableH3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableH3.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Candidate characteristics around the electoral victory cutoff{c )-}\label{c -(}tab:smooth_win_council{c )-}
{res}{txt}
{com}.         tex \begin{c -(}center{c )-}
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}%
{res}{txt}
{com}.         tex {c -(}\normalsize
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c c c{c )-}
{res}{txt}
{com}.         tex \toprule[1.5pt]
{res}{txt}
{com}.         tex \multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}{c )-} & Mean &  Std. Dev. & Victory & CI 95\% &
{res}{txt}
{com}.         tex Obs. & Band. Obs.  & Bandwith & p-value \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8) \\
{res}{txt}
{com}.         tex \hline
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel A:Candidates' characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         
.         foreach x in $balance_all{c -(}      
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 sum `x'
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' rv2, all vce(cluster muni_code) 
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %9.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_cl)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval1_`x' : di %5.3f `e(pv_cl)'
{txt} 18{com}.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 19{com}.                 
.                 
.         {c )-}       

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}women {c |}{res}      1,757    .2140011    .4102444          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      510{col 34}      670{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.565{col 34}    6.565
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.763{col 34}   11.763
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.558{col 34}    0.558
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      412{col 34}      468

Outcome: women. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11304{col 33} .04695{col 43}2.4074{col 52}0.016{col 60} .021009{col 73} .205066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .11971{col 33} .04695{col 43}2.5495{col 52}0.011{col 60} .027682{col 73}  .21174
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .11971{col 33} .05437{col 43}2.2018{col 52}0.028{col 60} .013149{col 73} .226273
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}sanc_before {c |}{res}      1,757    .0278884    .1647001          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      501{col 34}      659{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.385{col 34}    6.385
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.585{col 34}   10.585
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.603{col 34}    0.603
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: sanc_before. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .02578{col 33} .02279{col 43}1.1311{col 52}0.258{col 60}-.018892{col 73} .070454
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03033{col 33} .02279{col 43}1.3308{col 52}0.183{col 60} -.01434{col 73} .075005
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03033{col 33} .02658{col 43}1.1411{col 52}0.254{col 60}-.021769{col 73} .082433
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}pol_exp_d {c |}{res}      1,756    .1970387    .3978751          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1756
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      761{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      461{col 34}      605{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.542{col 34}    5.542
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.293{col 34}   10.293
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.538{col 34}    0.538
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      399{col 34}      455

Outcome: pol_exp_d. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .07098{col 33} .05158{col 43}1.3761{col 52}0.169{col 60}-.030114{col 73} .172066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .08495{col 33} .05158{col 43}1.6470{col 52}0.100{col 60}-.016144{col 73} .186035
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .08495{col 33}  .0582{col 43}1.4596{col 52}0.144{col 60} -.02912{col 73} .199011
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}elec_exp_d {c |}{res}      1,756    .1218679    .3272263          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1756
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      761{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      497{col 34}      655{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.313{col 34}    6.313
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.107{col 34}   11.107
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.568{col 34}    0.568
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      403{col 34}      461

Outcome: elec_exp_d. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .04724{col 33} .04019{col 43}1.1754{col 52}0.240{col 60}-.031531{col 73}  .12601
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0534{col 33} .04019{col 43}1.3287{col 52}0.184{col 60}-.025371{col 73} .132169
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0534{col 33} .04669{col 43}1.1437{col 52}0.253{col 60}-.038114{col 73} .144913
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}all {c |}{res}      1,757    1.908367    4.722013          1        177

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      562{col 34}      746{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.838{col 34}    7.838
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.525{col 34}   11.525
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.680{col 34}    0.680
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      409{col 34}      466

Outcome: all. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .56067{col 33} .91169{col 43}0.6150{col 52}0.539{col 60}-1.22621{col 73} 2.34756
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .62635{col 33} .91169{col 43}0.6870{col 52}0.492{col 60}-1.16054{col 73} 2.41323
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .62635{col 33} 1.1158{col 43}0.5614{col 52}0.575{col 60} -1.5605{col 73} 2.81319
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
total_income {c |}{res}      1,757    7.084262    15.16056     .00075        150

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      539{col 34}      713{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.188{col 34}    7.188
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.931{col 34}   10.931
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.658{col 34}    0.658
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      401{col 34}      457

Outcome: total_income. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .58853{col 33} 3.0381{col 43}0.1937{col 52}0.846{col 60}-5.36604{col 73} 6.54309
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .49064{col 33} 3.0381{col 43}0.1615{col 52}0.872{col 60}-5.46393{col 73}  6.4452
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .49064{col 33} 3.5659{col 43}0.1376{col 52}0.891{col 60}-6.49839{col 73} 7.47966
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
donations_~l {c |}{res}      1,757    .7065935    .3192663   .0014114          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      453{col 34}      596{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.397{col 34}    5.397
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    9.340{col 34}    9.340
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.578{col 34}    0.578
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      448

Outcome: donations_total. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01384{col 33} .03883{col 43}0.3565{col 52}0.722{col 60} -.06227{col 73} .089955
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01982{col 33} .03883{col 43}0.5105{col 52}0.610{col 60}-.056288{col 73} .095937
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01982{col 33} .04451{col 43}0.4454{col 52}0.656{col 60}-.067409{col 73} .107059
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}family {c |}{res}      1,757    .4876014    .4699454          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      526{col 34}      691{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.922{col 34}    6.922
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.420{col 34}   13.420
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      474

Outcome: family. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06767{col 33} .05581{col 43}-1.2125{col 52}0.225{col 60} -.17706{col 73} .041715
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08048{col 33} .05581{col 43}-1.4420{col 52}0.149{col 60}-.189865{col 73}  .02891
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08048{col 33} .06341{col 43}-1.2692{col 52}0.204{col 60}-.204757{col 73} .043802
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~101 {c |}{res}        981    2.764647    4.095874      .0005       43.1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      366{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.271{col 34}    6.271
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.033{col 34}   10.033
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      259{col 34}      302

Outcome: cont_donor_101. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .91988{col 33} .78464{col 43}1.1724{col 52}0.241{col 60}-.617987{col 73} 2.45775
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} 1.0282{col 33} .78464{col 43}1.3105{col 52}0.190{col 60}-.509621{col 73} 2.56611
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} 1.0282{col 33} .92188{col 43}1.1154{col 52}0.265{col 60}-.778596{col 73} 2.83509
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~102 {c |}{res}      1,007    1.788718    4.090475     .00025         88

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      313{col 34}      432{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.806{col 34}    7.806
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.354{col 34}   13.354
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.585{col 34}    0.585
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      252{col 34}      298

Outcome: cont_donor_102. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.46534{col 33} .75653{col 43}-0.6151{col 52}0.538{col 60}-1.94811{col 73} 1.01743
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.38187{col 33} .75653{col 43}-0.5048{col 52}0.614{col 60}-1.86464{col 73}  1.1009
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.38187{col 33} .82264{col 43}-0.4642{col 52}0.643{col 60}-1.99422{col 73} 1.23048
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}contraloria {c |}{res}      1,757    .0094916    .0920524          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      525{col 34}      690{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.906{col 34}    6.906
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.581{col 34}   13.581
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.509{col 34}    0.509
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      475

Outcome: contraloria. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01223{col 33} .00866{col 43}1.4117{col 52}0.158{col 60}-.004749{col 73} .029204
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01376{col 33} .00866{col 43}1.5890{col 52}0.112{col 60}-.003213{col 73}  .03074
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01376{col 33} .00975{col 43}1.4118{col 52}0.158{col 60}-.005344{col 73} .032871
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}above_limit {c |}{res}      1,734    .2689333     .425948          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1734
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      754{col 34}      980{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      469{col 34}      610{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.763{col 34}    5.763
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.000{col 34}   10.000
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.576{col 34}    0.576
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      443

Outcome: above_lim. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03645{col 33} .05426{col 43}0.6719{col 52}0.502{col 60}-.069886{col 73} .142791
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04359{col 33} .05426{col 43}0.8035{col 52}0.422{col 60}-.062747{col 73}  .14993
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04359{col 33} .06304{col 43}0.6915{col 52}0.489{col 60}-.079963{col 73} .167146
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

{com}. 
. 
.         
.         *Table continue
.         tex \ Women & `mean_women' & `sd_women' & `beta2_women' & [`ser1_women',`ser2_women'] & `N_women' & `Neff_women' & `bw_women' & `pval2_women' \\
{res}{txt}
{com}.         tex \ Sanctioned & `mean_sanc_before' & `sd_sanc_before' & `beta2_sanc_before' & [`ser1_sanc_before',`ser2_sanc_before'] & `N_sanc_before' & `Neff_sanc_before' & `bw_sanc_before' & `pval2_sanc_before' \\
{res}{txt}
{com}.         tex \ Political experience & `mean_pol_exp_d' & `sd_pol_exp_d' & `beta2_pol_exp_d' & [`ser1_pol_exp_d',`ser2_pol_exp_d'] & `N_pol_exp_d' & `Neff_pol_exp_d' & `bw_pol_exp_d' & `pval2_pol_exp_d' \\
{res}{txt}
{com}.         tex \ Held office before & `mean_elec_exp_d' & `sd_elec_exp_d' & `beta2_elec_exp_d' & [`ser1_elec_exp_d',`ser2_elec_exp_d'] & `N_elec_exp_d' & `Neff_elec_exp_d' & `bw_elec_exp_d' & `pval2_elec_exp_d' \\
{res}{txt}
{com}.         tex \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel B: General funding covariates{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Donors (all) & `mean_all' & `sd_all' & `beta2_all' & [`ser1_all',`ser2_all'] & `N_all' & `Neff_all' & `bw_all' & `pval2_all' \\
{res}{txt}
{com}.         tex \ Campaign revenue & `mean_total_income' & `sd_total_income' & `beta2_total_income' & [`ser1_total_income',`ser2_total_income'] & `N_total_income' & `Neff_total_income' & `bw_total_income' & `pval2_total_income' \\
{res}{txt}
{com}.         tex \ Donations /Revenue & `mean_donations_total' & `sd_donations_total' & `beta2_donations_total' & [`ser1_donations_total',`ser2_donations_total'] & `N_donations_total' & `Neff_donations_total' & `bw_donations_total' & `pval2_donations_total' \\
{res}{txt}
{com}. 
.         tex \\
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel C: Donors characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Family & `mean_family' & `sd_family' & `beta2_family' & [`ser1_family',`ser2_family'] & `N_family' & `Neff_family' & `bw_family' & `pval2_family' \\
{res}{txt}
{com}.         tex \ Avg. Donation (non-family) & `mean_cont_donor_102' & `sd_cont_donor_102' & `beta2_cont_donor_102' & [`ser1_cont_donor_102',`ser2_cont_donor_102'] & `N_cont_donor_102' & `Neff_cont_donor_102' & `bw_cont_donor_102' & `pval2_cont_donor_102' \\
{res}{txt}
{com}.         tex \ Avg. Donation (family) & `mean_cont_donor_101' & `sd_cont_donor_101' & `beta2_cont_donor_101' & [`ser1_cont_donor_101',`ser2_cont_donor_101'] & `N_cont_donor_101' & `Neff_cont_donor_101' & `bw_cont_donor_101' & `pval2_cont_donor_101' \\
{res}{txt}
{com}.         tex \ Comptroller sanction & `mean_contraloria' & `sd_contraloria' & `beta2_contraloria' & [`ser1_contraloria',`ser2_contraloria'] & `N_contraloria' & `Neff_contraloria' & `bw_contraloria' & `pval2_contraloria' \\
{res}{txt}
{com}.         tex \ Above limit & `mean_above_lim' & `sd_above_lim' & `beta2_above_lim' & [`ser1_above_lim',`ser2_above_lim'] & `N_above_lim' & `Neff_above_lim' & `bw_above_lim' & `pval2_above_lim' \\
{res}{txt}
{com}. 
.         
.         tex \addlinespace
{res}{txt}
{com}.         tex \midrule[1 pt]
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \scriptsize{c -(}
{res}{txt}
{com}.         tex Columns 1 and 2 report the descriptive statistics. Column 3 reports local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth (reported in column 7). Columns 4 and 8 report 95\% robust confidence intervals and robust p-values computed following \citep{c -(}calonico_robust_2014{c )-}. Columns 5 and 6 report total observations and observations in optimal MSE bandwidth. Sanctioned indicates the candidate has been sanctioned by the Office of the Inspector General. Donors and Donations include the totals for non-family and family donors. Family is the fraction of donors who are family members of the candidate. Above limit is the fraction of donors contributing above the individual legal limit. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}center{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\TableH3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. global dir "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"
{txt}
{com}.                 
.                 use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
.         global balance_ind women sanc_before pol_exp_d elec_exp_d 
{txt}
{com}.         global balance_fin all total_income donations_total
{txt}
{com}.         global balance_donors family cont_donor_101 cont_donor_102 contraloria above_lim    
{txt}
{com}.         global balance_all $balance_ind $balance_fin $balance_donors
{txt}
{com}. 
. 
.         
.         texdoc close 
{txt}(texdoc not initialized; nothing to do)

{com}.         cap erase "$dir/Tables/TableH3.tex"
{txt}
{com}.         texdoc init "$dir/Tables/TableH3.tex", force
{res}{txt}(texdoc output file is C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\/Tables\TableH3.tex)
{res}{txt}
{com}. 
.         tex \begin{c -(}table{c )-}[tbph]
{res}{txt}
{com}.         tex \caption{c -(}Candidate characteristics around the electoral victory cutoff{c )-}\label{c -(}tab:smooth_win_council{c )-}
{res}{txt}
{com}.         tex \begin{c -(}center{c )-}
{res}{txt}
{com}.         tex \scalebox{c -(}.8{c )-}{c -(}%
{res}{txt}
{com}.         tex {c -(}\normalsize
{res}{txt}
{com}.         tex \begin{c -(}tabular{c )-}{c -(}l c c c c c c c c{c )-}
{res}{txt}
{com}.         tex \toprule[1.5pt]
{res}{txt}
{com}.         tex \multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}{c )-} & Mean &  Std. Dev. & Victory & CI 95\% &
{res}{txt}
{com}.         tex Obs. & Band. Obs.  & Bandwith & p-value \\
{res}{txt}
{com}.         tex & (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8) \\
{res}{txt}
{com}.         tex \hline
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel A:Candidates' characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace
{res}{txt}
{com}.         
.         foreach x in $balance_all{c -(}      
{txt}  2{com}.         
.                 *Summary statistics for the mean
.                 sum `x'
{txt}  3{com}.                         local mean_`x' : di %5.3f r(mean)
{txt}  4{com}.                         local sd_`x' : di %5.3f r(sd) 
{txt}  5{com}.                 
.                 *Regressions
.                 rdrobust `x' rv2, all vce(cluster muni_code) 
{txt}  6{com}.                 
.                 *Local's for the table
.                 local bw_`x' : di %9.2f `e(h_l)'
{txt}  7{com}.                 local ser_`x' = round(`e(se_tau_rb)',0.001)
{txt}  8{com}.                 local Neff_`x' = `e(N_h_l)'+`e(N_h_r)'
{txt}  9{com}.                 local N_`x' = `e(N)'
{txt} 10{com}.                 local poly_`x' = `e(p)'
{txt} 11{com}.                 local beta1_`x' : di %5.3f `e(tau_cl)'
{txt} 12{com}.                 local beta2_`x' : di %5.3f `e(tau_cl)'
{txt} 13{com}. 
.                 *Confidence intervals
.                         local ser1_`x' : di %5.3f `e(ci_l_rb)'
{txt} 14{com}.                         local ser2_`x' : di %5.3f `e(ci_r_rb)'
{txt} 15{com}.                         
. /* HERE*/       local em1_`x' = (`beta1_`x''/`mean_`x'')*100 
{txt} 16{com}.                         local em1_`x' : di %5.2f `em1_`x''
{txt} 17{com}.                         
.                 *P-values
.                 local pval1_`x' : di %5.3f `e(pv_cl)'
{txt} 18{com}.                 local pval2_`x' : di %5.3f `e(pv_rb)'
{txt} 19{com}.                 
.                 
.         {c )-}       

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}women {c |}{res}      1,757    .2140011    .4102444          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      510{col 34}      670{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.565{col 34}    6.565
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.763{col 34}   11.763
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.558{col 34}    0.558
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      412{col 34}      468

Outcome: women. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11304{col 33} .04695{col 43}2.4074{col 52}0.016{col 60} .021009{col 73} .205066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .11971{col 33} .04695{col 43}2.5495{col 52}0.011{col 60} .027682{col 73}  .21174
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .11971{col 33} .05437{col 43}2.2018{col 52}0.028{col 60} .013149{col 73} .226273
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}sanc_before {c |}{res}      1,757    .0278884    .1647001          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      501{col 34}      659{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.385{col 34}    6.385
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.585{col 34}   10.585
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.603{col 34}    0.603
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: sanc_before. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .02578{col 33} .02279{col 43}1.1311{col 52}0.258{col 60}-.018892{col 73} .070454
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03033{col 33} .02279{col 43}1.3308{col 52}0.183{col 60} -.01434{col 73} .075005
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03033{col 33} .02658{col 43}1.1411{col 52}0.254{col 60}-.021769{col 73} .082433
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}pol_exp_d {c |}{res}      1,756    .1970387    .3978751          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1756
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      761{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      461{col 34}      605{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.542{col 34}    5.542
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.293{col 34}   10.293
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.538{col 34}    0.538
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      399{col 34}      455

Outcome: pol_exp_d. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .07098{col 33} .05158{col 43}1.3761{col 52}0.169{col 60}-.030114{col 73} .172066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .08495{col 33} .05158{col 43}1.6470{col 52}0.100{col 60}-.016144{col 73} .186035
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .08495{col 33}  .0582{col 43}1.4596{col 52}0.144{col 60} -.02912{col 73} .199011
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}elec_exp_d {c |}{res}      1,756    .1218679    .3272263          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1756
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      761{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      497{col 34}      655{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.313{col 34}    6.313
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.107{col 34}   11.107
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.568{col 34}    0.568
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      403{col 34}      461

Outcome: elec_exp_d. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .04724{col 33} .04019{col 43}1.1754{col 52}0.240{col 60}-.031531{col 73}  .12601
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0534{col 33} .04019{col 43}1.3287{col 52}0.184{col 60}-.025371{col 73} .132169
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0534{col 33} .04669{col 43}1.1437{col 52}0.253{col 60}-.038114{col 73} .144913
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 9}all {c |}{res}      1,757    1.908367    4.722013          1        177

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      562{col 34}      746{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.838{col 34}    7.838
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   11.525{col 34}   11.525
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.680{col 34}    0.680
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      409{col 34}      466

Outcome: all. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .56067{col 33} .91169{col 43}0.6150{col 52}0.539{col 60}-1.22621{col 73} 2.34756
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .62635{col 33} .91169{col 43}0.6870{col 52}0.492{col 60}-1.16054{col 73} 2.41323
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .62635{col 33} 1.1158{col 43}0.5614{col 52}0.575{col 60} -1.5605{col 73} 2.81319
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
total_income {c |}{res}      1,757    7.084262    15.16056     .00075        150

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      539{col 34}      713{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.188{col 34}    7.188
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.931{col 34}   10.931
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.658{col 34}    0.658
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      401{col 34}      457

Outcome: total_income. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .58853{col 33} 3.0381{col 43}0.1937{col 52}0.846{col 60}-5.36604{col 73} 6.54309
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .49064{col 33} 3.0381{col 43}0.1615{col 52}0.872{col 60}-5.46393{col 73}  6.4452
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .49064{col 33} 3.5659{col 43}0.1376{col 52}0.891{col 60}-6.49839{col 73} 7.47966
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
donations_~l {c |}{res}      1,757    .7065935    .3192663   .0014114          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      453{col 34}      596{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.397{col 34}    5.397
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    9.340{col 34}    9.340
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.578{col 34}    0.578
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      448

Outcome: donations_total. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01384{col 33} .03883{col 43}0.3565{col 52}0.722{col 60} -.06227{col 73} .089955
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01982{col 33} .03883{col 43}0.5105{col 52}0.610{col 60}-.056288{col 73} .095937
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01982{col 33} .04451{col 43}0.4454{col 52}0.656{col 60}-.067409{col 73} .107059
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}family {c |}{res}      1,757    .4876014    .4699454          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      526{col 34}      691{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.922{col 34}    6.922
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.420{col 34}   13.420
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      474

Outcome: family. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06767{col 33} .05581{col 43}-1.2125{col 52}0.225{col 60} -.17706{col 73} .041715
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08048{col 33} .05581{col 43}-1.4420{col 52}0.149{col 60}-.189865{col 73}  .02891
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08048{col 33} .06341{col 43}-1.2692{col 52}0.204{col 60}-.204757{col 73} .043802
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~101 {c |}{res}        981    2.764647    4.095874      .0005       43.1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      366{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.271{col 34}    6.271
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.033{col 34}   10.033
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      259{col 34}      302

Outcome: cont_donor_101. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .91988{col 33} .78464{col 43}1.1724{col 52}0.241{col 60}-.617987{col 73} 2.45775
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} 1.0282{col 33} .78464{col 43}1.3105{col 52}0.190{col 60}-.509621{col 73} 2.56611
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} 1.0282{col 33} .92188{col 43}1.1154{col 52}0.265{col 60}-.778596{col 73} 2.83509
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
cont_don~102 {c |}{res}      1,007    1.788718    4.090475     .00025         88

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      313{col 34}      432{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    7.806{col 34}    7.806
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.354{col 34}   13.354
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.585{col 34}    0.585
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      252{col 34}      298

Outcome: cont_donor_102. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.46534{col 33} .75653{col 43}-0.6151{col 52}0.538{col 60}-1.94811{col 73} 1.01743
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.38187{col 33} .75653{col 43}-0.5048{col 52}0.614{col 60}-1.86464{col 73}  1.1009
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.38187{col 33} .82264{col 43}-0.4642{col 52}0.643{col 60}-1.99422{col 73} 1.23048
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}contraloria {c |}{res}      1,757    .0094916    .0920524          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      525{col 34}      690{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    6.906{col 34}    6.906
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   13.581{col 34}   13.581
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.509{col 34}    0.509
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      475

Outcome: contraloria. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01223{col 33} .00866{col 43}1.4117{col 52}0.158{col 60}-.004749{col 73} .029204
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01376{col 33} .00866{col 43}1.5890{col 52}0.112{col 60}-.003213{col 73}  .03074
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01376{col 33} .00975{col 43}1.4118{col 52}0.158{col 60}-.005344{col 73} .032871
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}above_limit {c |}{res}      1,734    .2689333     .425948          0          1

Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1734
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      754{col 34}      980{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      469{col 34}      610{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    5.763{col 34}    5.763
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}   10.000{col 34}   10.000
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.576{col 34}    0.576
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      443

Outcome: above_lim. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03645{col 33} .05426{col 43}0.6719{col 52}0.502{col 60}-.069886{col 73} .142791
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04359{col 33} .05426{col 43}0.8035{col 52}0.422{col 60}-.062747{col 73}  .14993
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04359{col 33} .06304{col 43}0.6915{col 52}0.489{col 60}-.079963{col 73} .167146
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code

{com}. 
. 
.         
.         *Table continue
.         tex \ Women & `mean_women' & `sd_women' & `beta2_women' & [`ser1_women',`ser2_women'] & `N_women' & `Neff_women' & `bw_women' & `pval2_women' \\
{res}{txt}
{com}.         tex \ Sanctioned & `mean_sanc_before' & `sd_sanc_before' & `beta2_sanc_before' & [`ser1_sanc_before',`ser2_sanc_before'] & `N_sanc_before' & `Neff_sanc_before' & `bw_sanc_before' & `pval2_sanc_before' \\
{res}{txt}
{com}.         tex \ Political experience & `mean_pol_exp_d' & `sd_pol_exp_d' & `beta2_pol_exp_d' & [`ser1_pol_exp_d',`ser2_pol_exp_d'] & `N_pol_exp_d' & `Neff_pol_exp_d' & `bw_pol_exp_d' & `pval2_pol_exp_d' \\
{res}{txt}
{com}.         tex \ Held office before & `mean_elec_exp_d' & `sd_elec_exp_d' & `beta2_elec_exp_d' & [`ser1_elec_exp_d',`ser2_elec_exp_d'] & `N_elec_exp_d' & `Neff_elec_exp_d' & `bw_elec_exp_d' & `pval2_elec_exp_d' \\
{res}{txt}
{com}.         tex \\
{res}{txt}
{com}.         
.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel B: General funding covariates{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Donors (all) & `mean_all' & `sd_all' & `beta2_all' & [`ser1_all',`ser2_all'] & `N_all' & `Neff_all' & `bw_all' & `pval2_all' \\
{res}{txt}
{com}.         tex \ Campaign revenue & `mean_total_income' & `sd_total_income' & `beta2_total_income' & [`ser1_total_income',`ser2_total_income'] & `N_total_income' & `Neff_total_income' & `bw_total_income' & `pval2_total_income' \\
{res}{txt}
{com}.         tex \ Donations /Revenue & `mean_donations_total' & `sd_donations_total' & `beta2_donations_total' & [`ser1_donations_total',`ser2_donations_total'] & `N_donations_total' & `Neff_donations_total' & `bw_donations_total' & `pval2_donations_total' \\
{res}{txt}
{com}. 
.         tex \\
{res}{txt}
{com}.         tex \multicolumn{c -(}6{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Panel C: Donors characteristics{c )-}{c )-}\\
{res}{txt}
{com}.         tex \addlinespace       
{res}{txt}
{com}.         tex \ Family & `mean_family' & `sd_family' & `beta2_family' & [`ser1_family',`ser2_family'] & `N_family' & `Neff_family' & `bw_family' & `pval2_family' \\
{res}{txt}
{com}.         tex \ Avg. Donation (non-family) & `mean_cont_donor_102' & `sd_cont_donor_102' & `beta2_cont_donor_102' & [`ser1_cont_donor_102',`ser2_cont_donor_102'] & `N_cont_donor_102' & `Neff_cont_donor_102' & `bw_cont_donor_102' & `pval2_cont_donor_102' \\
{res}{txt}
{com}.         tex \ Avg. Donation (family) & `mean_cont_donor_101' & `sd_cont_donor_101' & `beta2_cont_donor_101' & [`ser1_cont_donor_101',`ser2_cont_donor_101'] & `N_cont_donor_101' & `Neff_cont_donor_101' & `bw_cont_donor_101' & `pval2_cont_donor_101' \\
{res}{txt}
{com}.         tex \ Comptroller sanction & `mean_contraloria' & `sd_contraloria' & `beta2_contraloria' & [`ser1_contraloria',`ser2_contraloria'] & `N_contraloria' & `Neff_contraloria' & `bw_contraloria' & `pval2_contraloria' \\
{res}{txt}
{com}.         tex \ Above limit & `mean_above_lim' & `sd_above_lim' & `beta2_above_lim' & [`ser1_above_lim',`ser2_above_lim'] & `N_above_lim' & `Neff_above_lim' & `bw_above_lim' & `pval2_above_lim' \\
{res}{txt}
{com}. 
.         
.         tex \addlinespace
{res}{txt}
{com}.         tex \midrule[1 pt]
{res}{txt}
{com}.         tex \end{c -(}tabular{c )-}
{res}{txt}
{com}.         tex {c )-}{c )-}
{res}{txt}
{com}.         tex \parbox{c -(}160mm{c )-}{c -(} \scriptsize{c -(}
{res}{txt}
{com}.         tex Columns 1 and 2 report the descriptive statistics. Column 3 reports local linear estimates of average treatment effects at the cutoff estimated with triangular kernel weights and optimal MSE bandwidth (reported in column 7). Columns 4 and 8 report 95\% robust confidence intervals and robust p-values computed following \citep{c -(}calonico_robust_2014{c )-}. Columns 5 and 6 report total observations and observations in optimal MSE bandwidth. Sanctioned indicates the candidate has been sanctioned by the Office of the Inspector General. Donors and Donations include the totals for non-family and family donors. Family is the fraction of donors who are family members of the candidate. Above limit is the fraction of donors contributing above the individual legal limit. 
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex {c )-}
{res}{txt}
{com}.         tex \end{c -(}center{c )-}
{res}{txt}
{com}.         tex \end{c -(}table{c )-}
{res}{txt}
{com}.         cap texdoc close
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\Fig1_D2_D4_D6.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. *figure1
. rdplot nfcontract margin_victory, p(3)
{res}
RD Plot with evenly spaced mimicking variance number of bins using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      450
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       30{col 37}       22
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.012{col 37}    0.017
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.012{col 37}    0.017
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}        7
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       30{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   10.000{col 37}    3.143
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.031
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.969
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot fcontract margin_victory, p(3)
{res}
RD Plot with evenly spaced mimicking variance number of bins using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}        6{col 37}       22
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.054{col 37}    0.017
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.054{col 37}    0.017
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        6{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.200{col 37}    4.400
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.367{col 37}    0.012
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.633{col 37}    0.988
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
. 
. *Figure D2a
. rdplot donate_15any margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1150
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      632
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      631
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       26{col 37}       22
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.014{col 37}    0.017
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.006{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       18{col 37}        6
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       26{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.444{col 37}    3.667
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.249{col 37}    0.020
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.751{col 37}    0.980
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D2b
. rdplot b5 margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1150
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      632
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      631
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: b5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       24{col 37}       23
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.015{col 37}    0.017
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.007
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        6{col 37}       15
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       24{col 37}       23
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    4.000{col 37}    1.533
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.015{col 37}    0.217
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.985{col 37}    0.783
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
. *Figure D4a
. rdplot nfcontract margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      450
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       18{col 37}       19
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.020{col 37}    0.020
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.009{col 37}    0.010
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        9{col 37}       23
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       18{col 37}       19
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    0.826
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.111{col 37}    0.639
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.889{col 37}    0.361
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D4b
. rdplot fcontract margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       18{col 37}       18
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.018{col 37}    0.021
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.009{col 37}    0.009
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       21{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       18{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    0.857{col 37}    4.500
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.614{col 37}    0.011
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.386{col 37}    0.989
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D4c
. rdplot fgot_above_ext margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       18{col 37}       17
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.018{col 37}    0.023
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.009{col 37}    0.010
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        9{col 37}       10
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       18{col 37}       17
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    1.700
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.111{col 37}    0.169
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.889{col 37}    0.831
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D4d
. rdplot fruns_any margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       18{col 37}       18
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.018{col 37}    0.021
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.009{col 37}    0.009
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        9{col 37}       12
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       18{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    1.500
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.111{col 37}    0.229
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.889{col 37}    0.771
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
. *Figure D6a
. rdplot fdonate_15any margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.017{col 37}    0.021
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.008{col 37}    0.009
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       13{col 37}       19
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.462{col 37}    0.947
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.243{col 37}    0.540
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.757{col 37}    0.460
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D6b
. rdplot nfdonate_15any margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      450
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       21{col 37}       17
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.017{col 37}    0.023
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.008{col 37}    0.010
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       19{col 37}       21
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       21{col 37}       17
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.105{col 37}    0.810
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.425{col 37}    0.653
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.575{col 37}    0.347
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D6c
. rdplot fb5 margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      438
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.324{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.017{col 37}    0.021
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.008{col 37}    0.009
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       11{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.727{col 37}    3.600
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.163{col 37}    0.021
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.837{col 37}    0.979
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure D6d
. rdplot nfb5 margin_victory ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      450
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.354{col 37}    0.383
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.019{col 37}    0.021
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.010{col 37}    0.011
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        8{col 37}       12
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       19{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.375{col 37}    1.500
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.069{col 37}    0.229
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.931{col 37}    0.771
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\FigC1-H3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
. *Figure C1
. rddensity margin_victory,plot
{res}Computing data-driven bandwidth selectors.

Point estimates and standard errors have been adjusted for repeated observations.
(Use option {it:nomasspoints} to suppress this adjustment.)

RD Manipulation test using local polynomial density estimation.

{txt}{ralign 9: c = }{res}    0.000{col 19} {c |}{col 22}{txt}Left of c{col 33}Right of c{col 53}Number of obs = {res}        1150
{txt}{hline 19}{c +}{hline 22}{col 53}Model         = {res}{ralign 12:unrestricted}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 53}{txt}BW method     = {res}{ralign 12:comb}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      419{col 34}      510{col 53}{txt}Kernel        = {res}{ralign 12:triangular}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        2{col 34}        2{col 53}{txt}VCE method    = {res}{ralign 12:jackknife}
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        3{col 34}        3
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.143

Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 22}
{ralign 18:Method}{col 19} {c |} {col 23}    T{col 38}P>|T|
{hline 19}{c +}{hline 22}
{ralign 18:Robust}{col 19} {c |} {col 21}{res}   0.9390{col 34}   0.3477
{txt}{hline 19}{c BT}{hline 22}

{res}P-values of binomial tests.{txt} (H0: prob = .5)
{hline 19}{c TT}{hline 22}{c TT}{hline 10}
{ralign 18: Window Length / 2}{col 20}{c |}{ralign 9: <c}{col 33}{ralign 9: >=c}{col 43}{c |}{col 49}P>|T|
{hline 19}{c +}{hline 22}{c +}{hline 10}
{res}{col 10}    0.004{col 20}{c |}       21{col 33}       20{col 43}{c |}{col 45}   1.0000
{col 10}    0.009{col 20}{c |}       42{col 33}       46{col 43}{c |}{col 45}   0.7493
{col 10}    0.013{col 20}{c |}       64{col 33}       73{col 43}{c |}{col 45}   0.4944
{col 10}    0.018{col 20}{c |}       80{col 33}       95{col 43}{c |}{col 45}   0.2899
{col 10}    0.022{col 20}{c |}      100{col 33}      113{col 43}{c |}{col 45}   0.4110
{col 10}    0.027{col 20}{c |}      121{col 33}      134{col 43}{c |}{col 45}   0.4524
{col 10}    0.031{col 20}{c |}      130{col 33}      157{col 43}{c |}{col 45}   0.1247
{col 10}    0.036{col 20}{c |}      145{col 33}      172{col 43}{c |}{col 45}   0.1441
{col 10}    0.040{col 20}{c |}      167{col 33}      194{col 43}{c |}{col 45}   0.1711
{col 10}    0.045{col 20}{c |}      186{col 33}      216{col 43}{c |}{col 45}   0.1480
{txt}{hline 19}{c BT}{hline 22}{c BT}{hline 10}
{res}{txt}
{com}. 
. 
. use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}. 
. *Figure H3
. rddensity rv2,plot
{res}Computing data-driven bandwidth selectors.

Point estimates and standard errors have been adjusted for repeated observations.
(Use option {it:nomasspoints} to suppress this adjustment.)

RD Manipulation test using local polynomial density estimation.

{txt}{ralign 9: c = }{res}    0.000{col 19} {c |}{col 22}{txt}Left of c{col 33}Right of c{col 53}Number of obs = {res}        1757
{txt}{hline 19}{c +}{hline 22}{col 53}Model         = {res}{ralign 12:unrestricted}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 53}{txt}BW method     = {res}{ralign 12:comb}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      408{col 34}      587{col 53}{txt}Kernel        = {res}{ralign 12:triangular}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        2{col 34}        2{col 53}{txt}VCE method    = {res}{ralign 12:jackknife}
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        3{col 34}        3
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    4.162{col 34}    5.326

Running variable: rv2.
{txt}{hline 19}{c TT}{hline 22}
{ralign 18:Method}{col 19} {c |} {col 23}    T{col 38}P>|T|
{hline 19}{c +}{hline 22}
{ralign 18:Robust}{col 19} {c |} {col 21}{res}  -0.0924{col 34}   0.9264
{txt}{hline 19}{c BT}{hline 22}

{res}P-values of binomial tests.{txt} (H0: prob = .5)
{hline 19}{c TT}{hline 22}{c TT}{hline 10}
{ralign 18: Window Length / 2}{col 20}{c |}{ralign 9: <c}{col 33}{ralign 9: >=c}{col 43}{c |}{col 49}P>|T|
{hline 19}{c +}{hline 22}{c +}{hline 10}
{res}{col 10}    0.206{col 20}{c |}       20{col 33}       38{col 43}{c |}{col 45}   0.0247
{col 10}    0.412{col 20}{c |}       53{col 33}       62{col 43}{c |}{col 45}   0.4558
{col 10}    0.617{col 20}{c |}       75{col 33}       94{col 43}{c |}{col 45}   0.1660
{col 10}    0.823{col 20}{c |}       99{col 33}      118{col 43}{c |}{col 45}   0.2217
{col 10}    1.029{col 20}{c |}      125{col 33}      152{col 43}{c |}{col 45}   0.1181
{col 10}    1.235{col 20}{c |}      146{col 33}      173{col 43}{c |}{col 45}   0.1454
{col 10}    1.440{col 20}{c |}      169{col 33}      202{col 43}{c |}{col 45}   0.0965
{col 10}    1.646{col 20}{c |}      188{col 33}      225{col 43}{c |}{col 45}   0.0764
{col 10}    1.852{col 20}{c |}      211{col 33}      254{col 43}{c |}{col 45}   0.0513
{col 10}    2.058{col 20}{c |}      236{col 33}      285{col 43}{c |}{col 45}   0.0354
{txt}{hline 19}{c BT}{hline 22}{c BT}{hline 10}
{res}{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\FigD1_D3_D5_E1-3.do"
{txt}
{com}. clear all
{res}{txt}
{com}. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. 
. 
.         global outcomes2 fcontract fgot_above_ext fruns_any
{txt}
{com}.         global outcomes3 donate_15any b5
{txt}
{com}.         global outcomes4 fdonate_15any fb5 
{txt}
{com}.         global outcomes5 nfdonate_15any nfb5
{txt}
{com}. 
.         
.         *Load data
. 
.         
.         ********************************************
.         *       DISCONTINUITY FIGURES
.         ********************************************
. 
.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}. 
.         *Define the level of confidence
.         local l = 95
{txt}
{com}.         
.         foreach x in nfcontract {c -(}
{txt}  2{com}.                 use  "$dir\Data\cand_level_persist_rep.dta",clear
{txt}  3{com}.                 drop if `x'==.
{txt}  4{com}.                 // Basic estimation and plot with degreee 1
.                 rdrobust `x' margin_victory, vce(cluster muni_code) p(1) bwselect(mserd) level(`l') 
{txt}  5{com}.                 local bw=round(`e(h_l)',0.001)
{txt}  6{com}.                 
.                 // Gen weights
.                 gen weights = .
{txt}  7{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory < 0 & margin_victory >= -`bw'
{txt}  8{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory >= 0 & margin_victory <= `bw'
{txt}  9{com}. 
.                 rdplot `x' margin_victory, vce(cluster muni_code) p(1) nbins(24 24) genvars h(`bw' `bw') scale(2 2) kernel(triangular)
{txt} 10{com}.                 // Not very nice with local linear
.                 gen bin_no=rdplot_id
{txt} 11{com}.                 gen meanx_bin=rdplot_mean_x
{txt} 12{com}.                 gen mean_ybin=rdplot_mean_y
{txt} 13{com}.                 sort bin_no margin_victory
{txt} 14{com}.                 bys bin_no: gen pos=_n
{txt} 15{com}.                 replace mean_ybin=. if pos!=1  // Keep the first value per bin to avoid pltting several equal means
{txt} 16{com}.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) (lpolyci `x' margin_victory if margin_victory<0 & abs(margin_victory)<=`bw', level(`l') kernel(triangle) bw(`bw') deg(1) fcolor(none)) (lpolyci `x' margin_victory if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') bw(`bw') kernel(triangle) deg(1) fcolor(none)), xline(0)  legend(off)
{txt} 17{com}.                 
.                 // Global linear as rdplot does
.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) /// 
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory<0 & abs(margin_victory)<=`bw', ciplot(rline) level(`l') fcolor(none))  ///
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') ciplot(rline) fcolor(none)), ///
>                                          xline(0)  legend(off)   graphregion(fcolor(white)) ///
>                                          xtitle(Margin Victory) 
{txt} 18{com}.                                          
.                 graph export "Fig_D3_`x'.pdf", replace
{txt} 19{com}.                 drop rdplot_id - pos weights
{txt} 20{com}.         {c )-}
{txt}(456 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      201{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.110{col 34}    0.110
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      256{col 34}      304

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08876{col 33} .04149{col 43}2.1394{col 52}0.032{col 60} .007442{col 73} .170068
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}1.9436{col 52}0.052{col 60}-.000802{col 73} .190711
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,133 missing values generated)
(180 real changes made)
(201 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      180{col 37}      201
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.067{col 37}    0.067
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}        7
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       30{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   16.000{col 37}    6.857
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.003
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    0.997
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(310 missing values generated)
(310 missing values generated)
(310 missing values generated)
(745 real changes made, 745 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D3_nfcontract.pdf{rm}
saved as
PDF
format
{p_end}

{com}. 
.                 foreach x in $outcomes2 {c -(}
{txt}  2{com}.                 use  "$dir\Data\cand_level_persist_rep.dta",clear
{txt}  3{com}.                 drop if `x'==.
{txt}  4{com}.                 // Basic estimation and plot with degreee 1
.                 rdrobust `x' margin_victory, vce(cluster muni_code) p(1) bwselect(mserd) level(`l') 
{txt}  5{com}.                 local bw=round(`e(h_l)',0.001)
{txt}  6{com}.                 
.                 // Gen weights
.                 gen weights = .
{txt}  7{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory < 0 & margin_victory >= -`bw'
{txt}  8{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory >= 0 & margin_victory <= `bw'
{txt}  9{com}. 
.                 rdplot `x' margin_victory, vce(cluster muni_code) p(1) nbins(24 24) genvars h(`bw' `bw') scale(2 2) kernel(triangular)
{txt} 10{com}.                 // Not very nice with local linear
.                 gen bin_no=rdplot_id
{txt} 11{com}.                 gen meanx_bin=rdplot_mean_x
{txt} 12{com}.                 gen mean_ybin=rdplot_mean_y
{txt} 13{com}.                 sort bin_no margin_victory
{txt} 14{com}.                 bys bin_no: gen pos=_n
{txt} 15{com}.                 replace mean_ybin=. if pos!=1  // Keep the first value per bin to avoid pltting several equal means
{txt} 16{com}.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) (lpolyci `x' margin_victory if margin_victory<0 & abs(margin_victory)<=`bw', level(`l') kernel(triangle) bw(`bw') deg(1) fcolor(none)) (lpolyci `x' margin_victory if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') bw(`bw') kernel(triangle) deg(1) fcolor(none)), xline(0)  legend(off)
{txt} 17{com}.                 
.                 // Global linear as rdplot does
.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) /// 
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory<0 & abs(margin_victory)<=`bw', ciplot(rline) level(`l') fcolor(none))  ///
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') ciplot(rline) fcolor(none)), ///
>                                          xline(0)  legend(off)   graphregion(fcolor(white)) ///
>                                          xtitle(Margin Victory) 
{txt} 18{com}.                                          
.                 graph export "Fig_D3_`x'.pdf", replace
{txt} 19{com}.                 drop rdplot_id - pos weights
{txt} 20{com}.         {c )-}
{txt}(537 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       86{col 34}      103{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.030{col 34}    0.030
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.115{col 34}    0.115
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      314

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00086{col 33} .00086{col 43}-0.9998{col 52}0.317{col 60}-.002554{col 73} .000828
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.4185{col 52}0.676{col 60}-.002828{col 73} .001833
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,052 missing values generated)
(86 real changes made)
(104 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}       86{col 37}      104
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.030{col 37}    0.030
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        6{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}    9.600
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(274 missing values generated)
(274 missing values generated)
(274 missing values generated)
(703 real changes made, 703 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D3_fcontract.pdf{rm}
saved as
PDF
format
{p_end}
(537 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      223{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      315

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03591{col 33} .04692{col 43}-0.7652{col 52}0.444{col 60}-.127877{col 73} .056061
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.8651{col 52}0.387{col 60}-.154678{col 73} .059948
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,052 missing values generated)
(180 real changes made)
(223 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      180{col 37}      223
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.070{col 37}    0.070
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        4{col 37}        6
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       20{col 37}       23
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   12.000{col 37}    8.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.002
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.998
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(274 missing values generated)
(274 missing values generated)
(274 missing values generated)
(703 real changes made, 703 to missing)
{res}{txt}note: label truncated to 80 characters
{res}{txt}note: label truncated to 80 characters
{res}{txt}{p 0 4 2}
file {bf}
Fig_D3_fgot_above_ext.pdf{rm}
saved as
PDF
format
{p_end}
(537 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      202{col 34}      254{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.082{col 34}    0.082
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      265{col 34}      319

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01966{col 33} .02008{col 43}-0.9789{col 52}0.328{col 60} -.05902{col 73} .019702
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-0.8473{col 52}0.397{col 60}-.060815{col 73} .024104
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,052 missing values generated)
(202 real changes made)
(254 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      202{col 37}      254
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.082{col 37}    0.082
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        3
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       40{col 37}       12
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}   16.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(274 missing values generated)
(274 missing values generated)
(274 missing values generated)
(703 real changes made, 703 to missing)
{res}{txt}note: label truncated to 80 characters
{res}{txt}note: label truncated to 80 characters
{res}{txt}{p 0 4 2}
file {bf}
Fig_D3_fruns_any.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
. 
.                 
. 
.         *Define the level of confidence
.         local l = 95
{txt}
{com}.         
.         foreach x in $outcomes3 {c -(}
{txt}  2{com}.                 use  "$dir\Data\cand_level_persist_rep.dta",clear
{txt}  3{com}.                 drop if `x'==.
{txt}  4{com}.                 // Basic estimation and plot with degreee 1
.                 rdrobust `x' margin_victory, vce(cluster muni_code) p(1) bwselect(mserd) level(`l') 
{txt}  5{com}.                 local bw=round(`e(h_l)',0.001)
{txt}  6{com}.                 
.                 // Gen weights
.                 gen weights = .
{txt}  7{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory < 0 & margin_victory >= -`bw'
{txt}  8{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory >= 0 & margin_victory <= `bw'
{txt}  9{com}. 
.                 rdplot `x' margin_victory, vce(cluster muni_code) p(1) nbins(24 24) genvars h(`bw' `bw') scale(2 2) kernel(triangular)
{txt} 10{com}.                 // Not very nice with local linear
.                 gen bin_no=rdplot_id
{txt} 11{com}.                 gen meanx_bin=rdplot_mean_x
{txt} 12{com}.                 gen mean_ybin=rdplot_mean_y
{txt} 13{com}.                 sort bin_no margin_victory
{txt} 14{com}.                 bys bin_no: gen pos=_n
{txt} 15{com}.                 replace mean_ybin=. if pos!=1  // Keep the first value per bin to avoid pltting several equal means
{txt} 16{com}.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) (lpolyci `x' margin_victory if margin_victory<0 & abs(margin_victory)<=`bw', level(`l') kernel(triangle) bw(`bw') deg(1) fcolor(none)) (lpolyci `x' margin_victory if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') bw(`bw') kernel(triangle) deg(1) fcolor(none)), xline(0)  legend(off)
{txt} 17{com}.                 
.                 // Global linear as rdplot does
.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) /// 
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory<0 & abs(margin_victory)<=`bw', ciplot(rline) level(`l') fcolor(none))  ///
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') ciplot(rline) fcolor(none)), ///
>                                          xline(0)  legend(off)   graphregion(fcolor(white)) ///
>                                          xtitle(Margin Victory) 
{txt} 18{com}.                                          
.                 graph export "Fig_D1_`x'.pdf", replace
{txt} 19{com}.                 drop rdplot_id - pos weights
{txt} 20{com}.         {c )-}
{txt}(0 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      327{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      413{col 34}      492

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13972{col 33} .03956{col 43}-3.5318{col 52}0.000{col 60}-.217256{col 73}-.062182
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.4091{col 52}0.001{col 60}-.241036{col 73}-.065058
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,589 missing values generated)
(284 real changes made)
(329 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1150
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      632
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      284{col 37}      329
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.072{col 37}    0.072
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       33{col 37}       27
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}   12.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(439 missing values generated)
(439 missing values generated)
(439 missing values generated)
(1,069 real changes made, 1,069 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D1_donate_15any.pdf{rm}
saved as
PDF
format
{p_end}
(0 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      306{col 34}      357{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      443{col 34}      520

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11359{col 33} .03363{col 43}-3.3771{col 52}0.001{col 60}-.179511{col 73}-.047665
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.2711{col 52}0.001{col 60}-.200497{col 73}-.050253
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,589 missing values generated)
(306 real changes made)
(354 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1150
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      518{col 37}      632
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      306{col 37}      354
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.077{col 37}    0.077
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: b5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       31{col 37}       27
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   16.000{col 37}    9.600
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(439 missing values generated)
(439 missing values generated)
(439 missing values generated)
(1,069 real changes made, 1,069 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D1_b5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
. 
. 
. 
.         *Define the level of confidence
.         local l = 95
{txt}
{com}.         
.                 
.         foreach x in $outcomes5 {c -(}
{txt}  2{com}.                 use  "$dir\Data\cand_level_persist_rep.dta",clear
{txt}  3{com}.                 drop if `x'==.
{txt}  4{com}.                 // Basic estimation and plot with degreee 1
.                 rdrobust `x' margin_victory, vce(cluster muni_code) p(1) bwselect(mserd) level(`l') 
{txt}  5{com}.                 local bw=round(`e(h_l)',0.001)
{txt}  6{com}.                 
.                 // Gen weights
.                 gen weights = .
{txt}  7{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory < 0 & margin_victory >= -`bw'
{txt}  8{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory >= 0 & margin_victory <= `bw'
{txt}  9{com}. 
.                 rdplot `x' margin_victory, vce(cluster muni_code) p(1) nbins(24 24) genvars h(`bw' `bw') scale(2 2) kernel(triangular)
{txt} 10{com}.                 // Not very nice with local linear
.                 gen bin_no=rdplot_id
{txt} 11{com}.                 gen meanx_bin=rdplot_mean_x
{txt} 12{com}.                 gen mean_ybin=rdplot_mean_y
{txt} 13{com}.                 sort bin_no margin_victory
{txt} 14{com}.                 bys bin_no: gen pos=_n
{txt} 15{com}.                 replace mean_ybin=. if pos!=1  // Keep the first value per bin to avoid pltting several equal means
{txt} 16{com}.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) (lpolyci `x' margin_victory if margin_victory<0 & abs(margin_victory)<=`bw', level(`l') kernel(triangle) bw(`bw') deg(1) fcolor(none)) (lpolyci `x' margin_victory if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') bw(`bw') kernel(triangle) deg(1) fcolor(none)), xline(0)  legend(off)
{txt} 17{com}.                 
.                 // Global linear as rdplot does
.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) /// 
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory<0 & abs(margin_victory)<=`bw', ciplot(rline) level(`l') fcolor(none))  ///
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') ciplot(rline) fcolor(none)), ///
>                                          xline(0)  legend(off)   graphregion(fcolor(white)) ///
>                                          xtitle(Margin Victory) 
{txt} 18{com}.                                          
.                 graph export "Fig_D5_`x'.pdf", replace
{txt} 19{com}.                 drop rdplot_id - pos weights
{txt} 20{com}.         {c )-}
{txt}(456 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      245{col 34}      287{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      404

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05392{col 33} .04088{col 43}-1.3189{col 52}0.187{col 60}-.134041{col 73} .026207
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.2320{col 52}0.218{col 60}-.153548{col 73} .035019
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,133 missing values generated)
(245 real changes made)
(287 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      245{col 37}      287
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.104{col 37}    0.104
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       30{col 37}       21
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}   12.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(310 missing values generated)
(310 missing values generated)
(310 missing values generated)
(745 real changes made, 745 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D5_nfdonate_15any.pdf{rm}
saved as
PDF
format
{p_end}
(456 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      155{col 34}      175{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      247{col 34}      291

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07969{col 33} .05297{col 43}-1.5044{col 52}0.132{col 60}-.183502{col 73} .024129
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-1.6132{col 52}0.107{col 60}-.221849{col 73} .021531
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,133 missing values generated)
(155 real changes made)
(174 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       823
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      372{col 37}      451
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      155{col 37}      174
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.054{col 37}    0.054
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}        2
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       24{col 37}       19
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   16.000{col 37}   24.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(310 missing values generated)
(310 missing values generated)
(310 missing values generated)
(745 real changes made, 745 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D5_nfb5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
. 
.                 
.         foreach x in $outcomes4 {c -(}
{txt}  2{com}.                 use  "$dir\Data\cand_level_persist_rep.dta",clear
{txt}  3{com}.                 drop if `x'==.
{txt}  4{com}.                 // Basic estimation and plot with degreee 1
.                 rdrobust `x' margin_victory, vce(cluster muni_code) p(1) bwselect(mserd) level(`l') 
{txt}  5{com}.                 local bw=round(`e(h_l)',0.001)
{txt}  6{com}.                 
.                 // Gen weights
.                 gen weights = .
{txt}  7{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory < 0 & margin_victory >= -`bw'
{txt}  8{com}.                 replace weights = (1 - abs(margin_victory / `bw')) if margin_victory >= 0 & margin_victory <= `bw'
{txt}  9{com}. 
.                 rdplot `x' margin_victory, vce(cluster muni_code) p(1) nbins(24 24) genvars h(`bw' `bw') scale(2 2) kernel(triangular)
{txt} 10{com}.                 // Not very nice with local linear
.                 gen bin_no=rdplot_id
{txt} 11{com}.                 gen meanx_bin=rdplot_mean_x
{txt} 12{com}.                 gen mean_ybin=rdplot_mean_y
{txt} 13{com}.                 sort bin_no margin_victory
{txt} 14{com}.                 bys bin_no: gen pos=_n
{txt} 15{com}.                 replace mean_ybin=. if pos!=1  // Keep the first value per bin to avoid pltting several equal means
{txt} 16{com}.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) (lpolyci `x' margin_victory if margin_victory<0 & abs(margin_victory)<=`bw', level(`l') kernel(triangle) bw(`bw') deg(1) fcolor(none)) (lpolyci `x' margin_victory if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') bw(`bw') kernel(triangle) deg(1) fcolor(none)), xline(0)  legend(off)
{txt} 17{com}.                 
.                 // Global linear as rdplot does
.                 tw (scatter mean_ybin margin_victory if abs(margin_victory)<=`bw', mcolor(gs10)) /// 
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory<0 & abs(margin_victory)<=`bw', ciplot(rline) level(`l') fcolor(none))  ///
>                                          (lfitci `x' margin_victory [aw = weights] if margin_victory>=0 & abs(margin_victory)<=`bw', level(`l') ciplot(rline) fcolor(none)), ///
>                                          xline(0)  legend(off)   graphregion(fcolor(white)) ///
>                                          xtitle(Margin Victory) 
{txt} 18{com}.                                          
.                 graph export "Fig_D5_`x'.pdf", replace
{txt} 19{com}.                 drop rdplot_id - pos weights
{txt} 20{com}.         {c )-}
{txt}(537 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      238{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      251{col 34}      306

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.2015{col 33} .05735{col 43}-3.5135{col 52}0.000{col 60}-.313908{col 73}-.089097
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-2.9758{col 52}0.003{col 60}-.335614{col 73}-.069073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,052 missing values generated)
(189 real changes made)
(238 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      189{col 37}      238
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.074{col 37}    0.074
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       23{col 37}       18
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}    9.600
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(274 missing values generated)
(274 missing values generated)
(274 missing values generated)
(703 real changes made, 703 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D5_fdonate_15any.pdf{rm}
saved as
PDF
format
{p_end}
(537 observations deleted)
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      206{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      280{col 34}      349

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17469{col 33} .04849{col 43}-3.6023{col 52}0.000{col 60} -.26974{col 73}-.079645
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}    -{col 33}    -{col 43}-3.2416{col 52}0.001{col 60} -.29583{col 73} -.07289
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
(1,052 missing values generated)
(206 real changes made)
(263 real changes made)
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       778
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Triangular}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      339{col 37}      439
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      206{col 37}      263
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        1{col 37}        1
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}    0.084{col 37}    0.084
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    2.000{col 37}    2.000

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       48{col 37}       48
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.007{col 37}    0.008
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       22{col 37}       44
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    9.600{col 37}   12.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.001
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.999
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}(274 missing values generated)
(274 missing values generated)
(274 missing values generated)
(703 real changes made, 703 to missing)
{res}{txt}{p 0 4 2}
file {bf}
Fig_D5_fb5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
.         ********************************************
.         *       BANDWIDTH FIGURES
.         ********************************************
. 
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         **Here is where the running variable goes.
.         foreach x in margin_victory {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in nfcontract {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_E2_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      201{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.110{col 34}    0.110
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      256{col 34}      304

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08876{col 33} .04149{col 43}2.1394{col 52}0.032{col 60} .007442{col 73} .170068
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09495{col 33} .04149{col 43}2.2888{col 52}0.022{col 60} .013642{col 73} .176268
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09495{col 33} .04886{col 43}1.9436{col 52}0.052{col 60}-.000802{col 73} .190711
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      291{col 34}      350{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.219{col 34}    0.219
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      356{col 34}      427

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08463{col 33} .03155{col 43}2.6825{col 52}0.007{col 60} .022796{col 73} .146474
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09439{col 33} .03155{col 43}2.9917{col 52}0.003{col 60} .032554{col 73} .156232
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09439{col 33} .03739{col 43}2.5245{col 52}0.012{col 60} .021109{col 73} .167677
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      285{col 34}      343{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.211{col 34}    0.211
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      355{col 34}      426

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08469{col 33} .03206{col 43}2.6418{col 52}0.008{col 60} .021858{col 73} .147523
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09336{col 33} .03206{col 43}2.9124{col 52}0.004{col 60} .030532{col 73} .156197
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09336{col 33} .03774{col 43}2.4741{col 52}0.013{col 60} .019403{col 73} .167326
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      280{col 34}      329{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.203{col 34}    0.203
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      354{col 34}      424

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08467{col 33} .03262{col 43}2.5954{col 52}0.009{col 60} .020729{col 73} .148604
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09234{col 33} .03262{col 43}2.8306{col 52}0.005{col 60} .028403{col 73} .156278
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09234{col 33} .03815{col 43}2.4202{col 52}0.016{col 60} .017561{col 73}  .16712
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      273{col 34}      317{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.195{col 34}    0.195
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      349{col 34}      420

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08482{col 33} .03313{col 43}2.5606{col 52}0.010{col 60} .019897{col 73} .149745
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09192{col 33} .03313{col 43}2.7750{col 52}0.006{col 60}    .027{col 73} .156848
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09192{col 33} .03857{col 43}2.3831{col 52}0.017{col 60} .016323{col 73} .167524
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      310{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.187{col 34}    0.187
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      348{col 34}      417

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08474{col 33} .03367{col 43}2.5170{col 52}0.012{col 60} .018755{col 73} .150729
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09076{col 33} .03367{col 43}2.6957{col 52}0.007{col 60} .024769{col 73} .156743
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09076{col 33} .03906{col 43}2.3234{col 52}0.020{col 60} .014197{col 73} .167315
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      254{col 34}      301{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.178{col 34}    0.178
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      343{col 34}      408

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08499{col 33} .03425{col 43}2.4810{col 52}0.013{col 60} .017849{col 73} .152125
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .08991{col 33} .03425{col 43}2.6248{col 52}0.009{col 60} .022773{col 73} .157049
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .08991{col 33} .03962{col 43}2.2696{col 52}0.023{col 60} .012267{col 73} .167556
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      245{col 34}      287{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.170{col 34}    0.170
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      403

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08551{col 33} .03477{col 43}2.4593{col 52}0.014{col 60} .017362{col 73} .153658
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09055{col 33} .03477{col 43}2.6043{col 52}0.009{col 60} .022403{col 73} .158699
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09055{col 33} .04018{col 43}2.2539{col 52}0.024{col 60} .011809{col 73} .169293
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      241{col 34}      282{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.162{col 34}    0.162
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      333{col 34}      389

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08705{col 33} .03531{col 43}2.4650{col 52}0.014{col 60} .017836{col 73} .156267
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09226{col 33} .03531{col 43}2.6126{col 52}0.009{col 60} .023048{col 73} .161479
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09226{col 33} .04087{col 43}2.2576{col 52}0.024{col 60} .012163{col 73} .172364
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      235{col 34}      266{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.154{col 34}    0.154
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      321{col 34}      378

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  .0877{col 33} .03591{col 43}2.4421{col 52}0.015{col 60} .017316{col 73} .158087
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09212{col 33} .03591{col 43}2.5651{col 52}0.010{col 60} .021732{col 73} .162504
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09212{col 33} .04162{col 43}2.2132{col 52}0.027{col 60} .010542{col 73} .173695
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      234{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.146{col 34}    0.146
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      308{col 34}      367

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08759{col 33}  .0365{col 43}2.3999{col 52}0.016{col 60} .016056{col 73} .159127
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09096{col 33}  .0365{col 43}2.4922{col 52}0.013{col 60} .019425{col 73} .162496
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09096{col 33} .04252{col 43}2.1394{col 52}0.032{col 60} .007628{col 73} .174293
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      228{col 34}      255{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.137{col 34}    0.137
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      293{col 34}      351

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08785{col 33} .03729{col 43}2.3556{col 52}0.018{col 60} .014754{col 73} .160946
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09051{col 33} .03729{col 43}2.4269{col 52}0.015{col 60} .017413{col 73} .163605
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09051{col 33} .04349{col 43}2.0809{col 52}0.037{col 60} .005262{col 73} .175756
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      217{col 34}      245{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      285{col 34}      343

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08769{col 33} .03824{col 43}2.2935{col 52}0.022{col 60} .012752{col 73} .162637
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09089{col 33} .03824{col 43}2.3770{col 52}0.017{col 60} .015946{col 73} .165831
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09089{col 33} .04471{col 43}2.0327{col 52}0.042{col 60} .003251{col 73} .178526
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      204{col 34}      228{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.121{col 34}    0.121
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      276{col 34}      321

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  .0876{col 33} .03956{col 43}2.2146{col 52}0.027{col 60} .010074{col 73} .165129
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09155{col 33} .03956{col 43}2.3144{col 52}0.021{col 60} .014021{col 73} .169076
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09155{col 33} .04636{col 43}1.9747{col 52}0.048{col 60} .000684{col 73} .182414
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      188{col 34}      209{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      263{col 34}      310

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08863{col 33} .04094{col 43}2.1649{col 52}0.030{col 60} .008388{col 73}  .16887
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0943{col 33} .04094{col 43}2.3033{col 52}0.021{col 60} .014055{col 73} .174537
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0943{col 33} .04804{col 43}1.9630{col 52}0.050{col 60} .000144{col 73} .188448
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      176{col 34}      195{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      290

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .09046{col 33} .04225{col 43}2.1407{col 52}0.032{col 60} .007639{col 73} .173274
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09706{col 33} .04225{col 43}2.2970{col 52}0.022{col 60} .014241{col 73} .179876
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09706{col 33} .05001{col 43}1.9406{col 52}0.052{col 60}-.000968{col 73} .195085
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      164{col 34}      181{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      240{col 34}      277

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .09313{col 33} .04356{col 43}2.1380{col 52}0.033{col 60} .007755{col 73} .178512
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09779{col 33} .04356{col 43}2.2450{col 52}0.025{col 60} .012415{col 73} .183171
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09779{col 33} .05204{col 43}1.8791{col 52}0.060{col 60} -.00421{col 73} .199796
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      155{col 34}      174{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      234{col 34}      263

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  .0968{col 33} .04518{col 43}2.1424{col 52}0.032{col 60} .008245{col 73} .185354
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .10245{col 33} .04518{col 43}2.2675{col 52}0.023{col 60} .013894{col 73} .191002
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .10245{col 33} .05403{col 43}1.8962{col 52}0.058{col 60}-.003447{col 73} .208344
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      147{col 34}      162{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.080{col 34}    0.080
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      219{col 34}      247

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .10309{col 33}  .0473{col 43}2.1793{col 52}0.029{col 60} .010376{col 73} .195799
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .1102{col 33}  .0473{col 43}2.3297{col 52}0.020{col 60} .017491{col 73} .202914
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .1102{col 33} .05672{col 43}1.9430{col 52}0.052{col 60}-.000961{col 73} .221366
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      124{col 34}      145{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      197{col 34}      220

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .10982{col 33} .05051{col 43}2.1744{col 52}0.030{col 60} .010831{col 73} .208809
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .12092{col 33} .05051{col 43}2.3942{col 52}0.017{col 60} .021932{col 73}  .21991
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .12092{col 33}  .0613{col 43}1.9725{col 52}0.049{col 60}  .00077{col 73} .241072
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      112{col 34}      126{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      175{col 34}      194

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11736{col 33} .05457{col 43}2.1508{col 52}0.031{col 60} .010411{col 73} .224308
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .13148{col 33} .05457{col 43}2.4096{col 52}0.016{col 60} .024535{col 73} .238432
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .13148{col 33} .06704{col 43}1.9611{col 52}0.050{col 60} .000079{col 73} .262888
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       97{col 34}      109{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      157{col 34}      177

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  .1206{col 33} .05959{col 43}2.0238{col 52}0.043{col 60} .003806{col 73} .237403
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .13473{col 33} .05959{col 43}2.2608{col 52}0.024{col 60} .017927{col 73} .251524
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .13473{col 33} .07258{col 43}1.8562{col 52}0.063{col 60}-.007535{col 73} .276986
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       88{col 34}       94{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.029{col 34}    0.029
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.611{col 34}    0.611
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      138{col 34}      156

Outcome: nfcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .12252{col 33} .06594{col 43}1.8580{col 52}0.063{col 60}-.006724{col 73} .251767
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .13663{col 33} .06594{col 43}2.0720{col 52}0.038{col 60} .007386{col 73} .265877
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .13663{col 33} .07943{col 43}1.7201{col 52}0.085{col 60}-.019056{col 73} .292319
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 23
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 23.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E2_nfcontract.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         foreach y in $outcomes2 {c -(}
{txt}  2{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' margin_victory, all vce(cluster muni_code) p(1) level(95) 
{txt}  3{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  4{com}.                 local bw_double = `bw'*2
{txt}  5{com}.                 local bw_half = `bw'/2
{txt}  6{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  7{com}.                 local counter=1
{txt}  8{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt}  9{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 10{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 11{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 12{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 13{com}.                 while `j'>0 {c -(}
{txt} 14{com}.                         local counter = `counter'+1
{txt} 15{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 16{com}.                         rdrobust `y' margin_victory, all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 17{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 18{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 19{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 20{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 21{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 22{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 23{com}.                                 local j = 0
{txt} 24{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 25{com}.                                 local b = `bw_double'/`rho'
{txt} 26{com}.                                 rdrobust `y' margin_victory, all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 27{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 28{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 29{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 30{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 31{com}.                                         
.                         
.                         {c )-}
{txt} 32{com}.                         else {c -(}
{txt} 33{com}.                                 local j = 1
{txt} 34{com}.                         {c )-}   
{txt} 35{com}.         {c )-}
{txt} 36{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 37{com}.         forvalues i=1/`counter' {c -(}
{txt} 38{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 39{com}.                 mat graph[`i',2] = `b_`i''
{txt} 40{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 41{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 42{com}.                 
.         {c )-}
{txt} 43{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 44{com}.         preserve
{txt} 45{com}.         clear 
{txt} 46{com}.         svmat graph
{txt} 47{com}.         * graphs
.         local line_2 = round(`margin_victory_line2',0.001)
{txt} 48{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 49{com}.         
.         *Save graph
.         graph export "Fig_E2_`y'.pdf", as(pdf) replace
{txt} 50{com}.         
.         restore
{txt} 51{com}.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       86{col 34}      103{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.030{col 34}    0.030
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.115{col 34}    0.115
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      314

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00086{col 33} .00086{col 43}-0.9998{col 52}0.317{col 60}-.002554{col 73} .000828
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0005{col 33} .00086{col 43}-0.5768{col 52}0.564{col 60}-.002189{col 73} .001193
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0005{col 33} .00119{col 43}-0.4185{col 52}0.676{col 60}-.002828{col 73} .001833
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      163{col 34}      194{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.060{col 34}    0.060
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.233{col 34}    0.233
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      419

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00051{col 33} .00051{col 43}0.9908{col 52}0.322{col 60}-.000494{col 73} .001505
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00074{col 33} .00051{col 43}1.4568{col 52}0.145{col 60}-.000257{col 73} .001742
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00074{col 33} .00091{col 43}0.8167{col 52}0.414{col 60} -.00104{col 73} .002526
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      157{col 34}      182{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.055{col 34}    0.055
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.214{col 34}    0.214
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00041{col 33} .00042{col 43}0.9859{col 52}0.324{col 60}-.000406{col 73} .001227
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00064{col 33} .00042{col 43}1.5288{col 52}0.126{col 60} -.00018{col 73} .001453
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00064{col 33} .00087{col 43}0.7280{col 52}0.467{col 60}-.001078{col 73} .002351
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      145{col 34}      170{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.050{col 34}    0.050
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.194{col 34}    0.194
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      407

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00027{col 33} .00028{col 43}0.9682{col 52}0.333{col 60}-.000279{col 73} .000824
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00049{col 33} .00028{col 43}1.7584{col 52}0.079{col 60}-.000057{col 73} .001047
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00049{col 33} .00085{col 43}0.5835{col 52}0.560{col 60}-.001168{col 73} .002157
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      127{col 34}      150{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.045{col 34}    0.045
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.175{col 34}    0.175
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      319{col 34}      399

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} 5.4e-05{col 33} 9.2e-05{col 43}0.5870{col 52}0.557{col 60}-.000126{col 73} .000233
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0003{col 33} 9.2e-05{col 43}3.2437{col 52}0.001{col 60} .000118{col 73} .000476
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0003{col 33} .00086{col 43}0.3444{col 52}0.731{col 60}-.001393{col 73} .001987
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      109{col 34}      132{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.040{col 34}    0.040
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.155{col 34}    0.155
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      306{col 34}      381

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00021{col 33} .00023{col 43}-0.9396{col 52}0.347{col 60}-.000658{col 73} .000231
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} 5.6e-05{col 33} .00023{col 43}0.2468{col 52}0.805{col 60}-.000389{col 73}   .0005
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} 5.6e-05{col 33} .00093{col 43}0.0601{col 52}0.952{col 60}-.001769{col 73} .001881
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       92{col 34}      115{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.035{col 34}    0.035
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.136{col 34}    0.136
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      282{col 34}      350

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00054{col 33} .00054{col 43}-0.9907{col 52}0.322{col 60}  -.0016{col 73} .000526
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00023{col 33} .00054{col 43}-0.4262{col 52}0.670{col 60}-.001294{col 73} .000832
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00023{col 33} .00103{col 43}-0.2238{col 52}0.823{col 60}-.002256{col 73} .001794
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       86{col 34}      104{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.030{col 34}    0.030
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      315

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00084{col 33} .00084{col 43}-0.9995{col 52}0.318{col 60}-.002482{col 73} .000805
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00047{col 33} .00084{col 43}-0.5562{col 52}0.578{col 60} -.00211{col 73} .001177
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00047{col 33} .00117{col 43}-0.3981{col 52}0.691{col 60}-.002763{col 73}  .00183
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       74{col 34}       88{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.025{col 34}    0.025
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      224{col 34}      285

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00087{col 33} .00087{col 43}-0.9976{col 52}0.318{col 60}-.002585{col 73} .000841
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00062{col 33} .00087{col 43}-0.7094{col 52}0.478{col 60}-.002333{col 73} .001093
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00062{col 33} .00127{col 43}-0.4894{col 52}0.625{col 60}-.003103{col 73} .001863
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       60{col 34}       73{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.020{col 34}    0.020
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      198{col 34}      247

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}      0{col 33}      0{col 43}    .{col 52}    .{col 60}       0{col 73}       0
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00048{col 33}      0{col 43}    .{col 52}    .{col 60}-.000484{col 73}-.000484
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00048{col 33} .00075{col 43}-0.6495{col 52}0.516{col 60}-.001945{col 73} .000977
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       46{col 34}       55{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.015{col 34}    0.015
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.257{col 34}    0.257
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      162{col 34}      190

Outcome: fcontract. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}      0{col 33}      0{col 43}    .{col 52}    .{col 60}       0{col 73}       0
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-7.5e-05{col 33}      0{col 43}    .{col 52}    .{col 60}-.000075{col 73}-.000075
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-7.5e-05{col 33} .00021{col 43}-0.3475{col 52}0.728{col 60}-.000495{col 73} .000346
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 11
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 11.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E2_fcontract.pdf{rm}
saved as
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format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      223{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      315

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03591{col 33} .04692{col 43}-0.7652{col 52}0.444{col 60}-.127877{col 73} .056061
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04737{col 33} .04692{col 43}-1.0094{col 52}0.313{col 60}-.139334{col 73} .044604
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04737{col 33} .05475{col 43}-0.8651{col 52}0.387{col 60}-.154678{col 73} .059948
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      287{col 34}      355{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.140{col 34}    0.140
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.234{col 34}    0.234
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      419

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01793{col 33} .03366{col 43}-0.5325{col 52}0.594{col 60}-.083908{col 73} .048053
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03219{col 33} .03366{col 43}-0.9561{col 52}0.339{col 60}-.098168{col 73} .033794
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03219{col 33} .04187{col 43}-0.7688{col 52}0.442{col 60}-.114248{col 73} .049874
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      280{col 34}      349{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.135{col 34}    0.135
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.225{col 34}    0.225
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      417

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01886{col 33} .03415{col 43}-0.5522{col 52}0.581{col 60}-.085795{col 73} .048076
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03326{col 33} .03415{col 43}-0.9739{col 52}0.330{col 60}-.100197{col 73} .033674
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03326{col 33} .04231{col 43}-0.7862{col 52}0.432{col 60}-.116183{col 73}  .04966
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      345{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.130{col 34}    0.130
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.217{col 34}    0.217
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01956{col 33} .03473{col 43}-0.5631{col 52}0.573{col 60}-.087624{col 73} .048511
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03395{col 33} .03473{col 43}-0.9774{col 52}0.328{col 60}-.102013{col 73} .034122
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03395{col 33} .04278{col 43}-0.7935{col 52}0.427{col 60}-.117788{col 73} .049897
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      276{col 34}      332{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.125{col 34}    0.125
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.209{col 34}    0.209
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02021{col 33} .03549{col 43}-0.5694{col 52}0.569{col 60} -.08977{col 73} .049353
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03447{col 33} .03549{col 43}-0.9711{col 52}0.331{col 60}-.104029{col 73} .035095
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03447{col 33} .04334{col 43}-0.7952{col 52}0.426{col 60}-.119417{col 73} .050482
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      267{col 34}      320{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.120{col 34}    0.120
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.200{col 34}    0.200
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      328{col 34}      411

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02138{col 33} .03628{col 43}-0.5895{col 52}0.556{col 60}-.092481{col 73} .049715
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03582{col 33} .03628{col 43}-0.9874{col 52}0.323{col 60}-.106918{col 73} .035279
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03582{col 33} .04399{col 43}-0.8142{col 52}0.416{col 60}-.122043{col 73} .050404
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      260{col 34}      314{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.115{col 34}    0.115
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.192{col 34}    0.192
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      406

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02341{col 33} .03712{col 43}-0.6306{col 52}0.528{col 60}-.096166{col 73}  .04935
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03753{col 33} .03712{col 43}-1.0110{col 52}0.312{col 60}-.110288{col 73} .035228
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03753{col 33} .04467{col 43}-0.8401{col 52}0.401{col 60}-.125089{col 73} .050029
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      250{col 34}      306{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.110{col 34}    0.110
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.184{col 34}    0.184
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      326{col 34}      405

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02621{col 33} .03808{col 43}-0.6881{col 52}0.491{col 60} -.10085{col 73} .048438
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0396{col 33} .03808{col 43}-1.0397{col 52}0.298{col 60} -.11424{col 73} .035048
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0396{col 33} .04552{col 43}-0.8699{col 52}0.384{col 60}-.128812{col 73}  .04962
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      237{col 34}      297{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.175{col 34}    0.175
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      319{col 34}      400

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02905{col 33} .03895{col 43}-0.7459{col 52}0.456{col 60}-.105396{col 73} .047292
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04196{col 33} .03895{col 43}-1.0773{col 52}0.281{col 60}-.118305{col 73} .034383
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04196{col 33} .04636{col 43}-0.9051{col 52}0.365{col 60}-.132828{col 73} .048906
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      227{col 34}      291{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.100{col 34}    0.100
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.167{col 34}    0.167
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      314{col 34}      394

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03085{col 33} .03982{col 43}-0.7747{col 52}0.439{col 60}-.108898{col 73} .047199
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04329{col 33} .03982{col 43}-1.0872{col 52}0.277{col 60}-.121343{col 73} .034754
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04329{col 33} .04729{col 43}-0.9156{col 52}0.360{col 60}-.135978{col 73} .049388
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      220{col 34}      277{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.095{col 34}    0.095
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.159{col 34}    0.159
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      307{col 34}      383

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03305{col 33} .04072{col 43}-0.8118{col 52}0.417{col 60}-.112856{col 73} .046748
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04493{col 33} .04072{col 43}-1.1035{col 52}0.270{col 60} -.12473{col 73} .034873
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04493{col 33} .04824{col 43}-0.9313{col 52}0.352{col 60}-.139481{col 73} .049624
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      270{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.090{col 34}    0.090
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.150{col 34}    0.150
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      298{col 34}      374

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03526{col 33} .04156{col 43}-0.8485{col 52}0.396{col 60}-.116719{col 73} .046192
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04628{col 33} .04156{col 43}-1.1135{col 52}0.265{col 60}-.127733{col 73} .035177
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04628{col 33} .04933{col 43}-0.9382{col 52}0.348{col 60} -.14296{col 73} .050404
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      207{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.085{col 34}    0.085
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.142{col 34}    0.142
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      289{col 34}      358

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03676{col 33} .04272{col 43}-0.8606{col 52}0.389{col 60}-.120493{col 73} .046967
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04701{col 33} .04272{col 43}-1.1005{col 52}0.271{col 60}-.130743{col 73} .036717
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04701{col 33} .05056{col 43}-0.9298{col 52}0.352{col 60}-.146115{col 73} .052089
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      200{col 34}      252{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.080{col 34}    0.080
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      348

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03662{col 33} .04392{col 43}-0.8337{col 52}0.404{col 60}-.122708{col 73}  .04947
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0468{col 33} .04392{col 43}-1.0654{col 52}0.287{col 60}-.132888{col 73} .039291
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0468{col 33} .05166{col 43}-0.9060{col 52}0.365{col 60}-.148041{col 73} .054445
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      191{col 34}      238{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.075{col 34}    0.075
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.125{col 34}    0.125
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      277{col 34}      333

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03695{col 33} .04535{col 43}-0.8149{col 52}0.415{col 60}-.125837{col 73}  .05193
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04819{col 33} .04535{col 43}-1.0626{col 52}0.288{col 60}-.137071{col 73} .040696
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04819{col 33} .05305{col 43}-0.9084{col 52}0.364{col 60}-.152161{col 73} .055787
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      180{col 34}      223{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.070{col 34}    0.070
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      315

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03581{col 33} .04687{col 43}-0.7641{col 52}0.445{col 60}-.127677{col 73} .056051
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04733{col 33} .04687{col 43}-1.0097{col 52}0.313{col 60} -.13919{col 73} .044538
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04733{col 33} .05469{col 43}-0.8654{col 52}0.387{col 60}-.154516{col 73} .059863
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      170{col 34}      207{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.065{col 34}    0.065
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      245{col 34}      304

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03809{col 33} .04816{col 43}-0.7909{col 52}0.429{col 60}-.132488{col 73} .056308
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04819{col 33} .04816{col 43}-1.0005{col 52}0.317{col 60}-.142585{col 73} .046211
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04819{col 33} .05658{col 43}-0.8516{col 52}0.394{col 60}-.159085{col 73}  .06271
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      163{col 34}      194{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.060{col 34}    0.060
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.100{col 34}    0.100
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      227{col 34}      291

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04066{col 33} .04935{col 43}-0.8239{col 52}0.410{col 60}-.137386{col 73} .056069
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04999{col 33} .04935{col 43}-1.0129{col 52}0.311{col 60}-.146718{col 73} .046737
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04999{col 33}  .0583{col 43}-0.8574{col 52}0.391{col 60}-.164266{col 73} .064285
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      157{col 34}      182{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.055{col 34}    0.055
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      217{col 34}      272

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04456{col 33} .05093{col 43}-0.8750{col 52}0.382{col 60}-.144375{col 73} .055256
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05222{col 33} .05093{col 43}-1.0253{col 52}0.305{col 60}-.152031{col 73}   .0476
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05222{col 33}  .0602{col 43}-0.8674{col 52}0.386{col 60}  -.1702{col 73} .065769
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      145{col 34}      170{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.050{col 34}    0.050
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      204{col 34}      258

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04935{col 33} .05333{col 43}-0.9253{col 52}0.355{col 60} -.15388{col 73} .055183
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05734{col 33} .05333{col 43}-1.0751{col 52}0.282{col 60}-.161872{col 73} .047191
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05734{col 33}  .0631{col 43}-0.9088{col 52}0.363{col 60}-.181009{col 73} .066328
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      127{col 34}      150{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.045{col 34}    0.045
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.075{col 34}    0.075
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      191{col 34}      238

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06162{col 33} .05696{col 43}-1.0819{col 52}0.279{col 60}-.173254{col 73} .050012
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07279{col 33} .05696{col 43}-1.2781{col 52}0.201{col 60}-.184428{col 73} .038838
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07279{col 33} .06729{col 43}-1.0818{col 52}0.279{col 60}-.204681{col 73} .059091
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      109{col 34}      132{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.040{col 34}    0.040
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      173{col 34}      212

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07505{col 33} .06135{col 43}-1.2233{col 52}0.221{col 60}-.195286{col 73} .045193
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09266{col 33} .06135{col 43}-1.5104{col 52}0.131{col 60}-.212901{col 73} .027578
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09266{col 33} .07283{col 43}-1.2723{col 52}0.203{col 60}-.235409{col 73} .050086
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       92{col 34}      115{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.035{col 34}    0.035
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.599{col 34}    0.599
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      162{col 34}      190

Outcome: fgot_above_ext. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08732{col 33} .06678{col 43}-1.3075{col 52}0.191{col 60}-.218214{col 73} .043572
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10531{col 33} .06678{col 43}-1.5770{col 52}0.115{col 60}-.236207{col 73} .025579
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10531{col 33} .07792{col 43}-1.3515{col 52}0.177{col 60}-.258041{col 73} .047413
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 23
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 23.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E2_fgot_above_ext.pdf{rm}
saved as
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format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      202{col 34}      254{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.082{col 34}    0.082
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      265{col 34}      319

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01966{col 33} .02008{col 43}-0.9789{col 52}0.328{col 60} -.05902{col 73} .019702
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01836{col 33} .02008{col 43}-0.9140{col 52}0.361{col 60}-.057717{col 73} .021005
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01836{col 33} .02166{col 43}-0.8473{col 52}0.397{col 60}-.060815{col 73} .024104
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      311{col 34}      391{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.164{col 34}    0.164
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.237{col 34}    0.237
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      331{col 34}      421

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0187{col 33} .01682{col 43}-1.1118{col 52}0.266{col 60}-.051671{col 73} .014267
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02231{col 33} .01682{col 43}-1.3265{col 52}0.185{col 60}-.055283{col 73} .010656
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02231{col 33} .02055{col 43}-1.0861{col 52}0.277{col 60}-.062581{col 73} .017954
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      307{col 34}      384{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.159{col 34}    0.159
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.229{col 34}    0.229
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      418

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01864{col 33}   .017{col 43}-1.0965{col 52}0.273{col 60} -.05197{col 73} .014683
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02266{col 33}   .017{col 43}-1.3325{col 52}0.183{col 60}-.055984{col 73} .010669
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02266{col 33}  .0206{col 43}-1.0998{col 52}0.271{col 60}-.063034{col 73} .017719
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      304{col 34}      379{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.154{col 34}    0.154
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.222{col 34}    0.222
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      416

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01873{col 33}  .0172{col 43}-1.0888{col 52}0.276{col 60}-.052443{col 73} .014985
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0229{col 33}  .0172{col 43}-1.3311{col 52}0.183{col 60}-.056611{col 73} .010818
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0229{col 33} .02069{col 43}-1.1064{col 52}0.269{col 60}-.063455{col 73} .017662
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      297{col 34}      373{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.149{col 34}    0.149
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.215{col 34}    0.215
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01877{col 33} .01741{col 43}-1.0783{col 52}0.281{col 60}-.052896{col 73} .015351
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02247{col 33} .01741{col 43}-1.2905{col 52}0.197{col 60}-.056591{col 73} .011656
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02247{col 33} .02079{col 43}-1.0807{col 52}0.280{col 60}-.063217{col 73} .018281
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      292{col 34}      363{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.144{col 34}    0.144
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.208{col 34}    0.208
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      413

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01869{col 33} .01763{col 43}-1.0602{col 52}0.289{col 60}-.053234{col 73} .015859
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02189{col 33} .01763{col 43}-1.2419{col 52}0.214{col 60}-.056436{col 73} .012657
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02189{col 33} .02092{col 43}-1.0463{col 52}0.295{col 60}-.062893{col 73} .019114
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      285{col 34}      353{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.139{col 34}    0.139
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.201{col 34}    0.201
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      328{col 34}      411

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01888{col 33} .01784{col 43}-1.0579{col 52}0.290{col 60}-.053852{col 73} .016096
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02155{col 33} .01784{col 43}-1.2076{col 52}0.227{col 60}-.056523{col 73} .013426
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02155{col 33} .02105{col 43}-1.0235{col 52}0.306{col 60}-.062812{col 73} .019715
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      280{col 34}      349{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.193{col 34}    0.193
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      407

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01924{col 33} .01805{col 43}-1.0657{col 52}0.287{col 60}-.054619{col 73} .016143
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02126{col 33} .01805{col 43}-1.1776{col 52}0.239{col 60}-.056638{col 73} .014124
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02126{col 33} .02116{col 43}-1.0045{col 52}0.315{col 60}-.062734{col 73} .020219
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      343{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.186{col 34}    0.186
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      326{col 34}      405

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01963{col 33} .01829{col 43}-1.0735{col 52}0.283{col 60}-.055473{col 73} .016211
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02092{col 33} .01829{col 43}-1.1442{col 52}0.253{col 60}-.056767{col 73} .014917
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02092{col 33} .02129{col 43}-0.9829{col 52}0.326{col 60}-.062649{col 73}   .0208
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      274{col 34}      331{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.179{col 34}    0.179
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      321{col 34}      403

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02004{col 33} .01857{col 43}-1.0788{col 52}0.281{col 60}-.056441{col 73} .016366
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02099{col 33} .01857{col 43}-1.1299{col 52}0.259{col 60} -.05739{col 73} .015417
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02099{col 33} .02144{col 43}-0.9791{col 52}0.328{col 60}-.062998{col 73} .021026
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      265{col 34}      319{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.172{col 34}    0.172
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      318{col 34}      399

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02034{col 33} .01884{col 43}-1.0796{col 52}0.280{col 60}-.057272{col 73} .016587
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02116{col 33} .01884{col 43}-1.1229{col 52}0.261{col 60}-.058087{col 73} .015771
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02116{col 33} .02155{col 43}-0.9819{col 52}0.326{col 60}-.063393{col 73} .021077
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      312{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.165{col 34}    0.165
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      311{col 34}      391

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02058{col 33} .01912{col 43}-1.0762{col 52}0.282{col 60}-.058056{col 73} .016899
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02134{col 33} .01912{col 43}-1.1163{col 52}0.264{col 60}-.058823{col 73} .016133
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02134{col 33} .02165{col 43}-0.9859{col 52}0.324{col 60}-.063777{col 73} .021087
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      245{col 34}      304{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.157{col 34}    0.157
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      307{col 34}      383

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02069{col 33}  .0194{col 43}-1.0666{col 52}0.286{col 60}-.058715{col 73} .017331
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02159{col 33}  .0194{col 43}-1.1130{col 52}0.266{col 60}-.059614{col 73} .016431
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02159{col 33} .02171{col 43}-0.9947{col 52}0.320{col 60}-.064133{col 73}  .02095
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      235{col 34}      296{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.150{col 34}    0.150
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      298{col 34}      373

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02064{col 33} .01959{col 43}-1.0535{col 52}0.292{col 60}-.059045{col 73}  .01776
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0215{col 33} .01959{col 43}-1.0974{col 52}0.272{col 60}-.059906{col 73}   .0169
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0215{col 33} .02171{col 43}-0.9906{col 52}0.322{col 60}-.064049{col 73} .021043
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      227{col 34}      289{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      291{col 34}      360

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02059{col 33} .01974{col 43}-1.0432{col 52}0.297{col 60}-.059288{col 73} .018099
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02185{col 33} .01974{col 43}-1.1066{col 52}0.268{col 60}-.060541{col 73} .016847
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02185{col 33} .02167{col 43}-1.0084{col 52}0.313{col 60}-.064311{col 73} .020617
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      218{col 34}      274{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.136{col 34}    0.136
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      282{col 34}      350

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02042{col 33} .01985{col 43}-1.0287{col 52}0.304{col 60}-.059318{col 73} .018482
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02113{col 33} .01985{col 43}-1.0644{col 52}0.287{col 60}-.060026{col 73} .017775
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02113{col 33} .02162{col 43}-0.9773{col 52}0.328{col 60}-.063493{col 73} .021242
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      269{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      342

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02013{col 33} .01993{col 43}-1.0104{col 52}0.312{col 60}-.059186{col 73}  .01892
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02004{col 33} .01993{col 43}-1.0059{col 52}0.314{col 60}-.059095{col 73} .019011
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02004{col 33} .02158{col 43}-0.9289{col 52}0.353{col 60}-.062329{col 73} .022246
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      206{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.121{col 34}    0.121
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      267{col 34}      323

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01963{col 33} .02005{col 43}-0.9790{col 52}0.328{col 60}-.058927{col 73}  .01967
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0186{col 33} .02005{col 43}-0.9275{col 52}0.354{col 60}-.057896{col 73} .020701
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0186{col 33} .02165{col 43}-0.8589{col 52}0.390{col 60}-.061034{col 73}  .02384
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      199{col 34}      249{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      258{col 34}      312

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01958{col 33} .02015{col 43}-0.9718{col 52}0.331{col 60} -.05907{col 73}  .01991
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01769{col 33} .02015{col 43}-0.8782{col 52}0.380{col 60}-.057185{col 73} .021796
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01769{col 33}  .0217{col 43}-0.8154{col 52}0.415{col 60}-.060226{col 73} .024837
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      238{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.107{col 34}    0.107
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      239{col 34}      299

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01937{col 33} .02024{col 43}-0.9568{col 52}0.339{col 60}-.059044{col 73} .020307
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01672{col 33} .02024{col 43}-0.8258{col 52}0.409{col 60}-.056393{col 73} .022958
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01672{col 33} .02177{col 43}-0.7679{col 52}0.443{col 60}-.059389{col 73} .025954
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      178{col 34}      218{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.100{col 34}    0.100
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      227{col 34}      291

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01905{col 33} .02028{col 43}-0.9394{col 52}0.348{col 60}-.058786{col 73} .020693
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01583{col 33} .02028{col 43}-0.7807{col 52}0.435{col 60} -.05557{col 73}  .02391
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01583{col 33} .02178{col 43}-0.7269{col 52}0.467{col 60}-.058516{col 73} .026855
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      169{col 34}      206{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      217{col 34}      272

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01845{col 33} .02022{col 43}-0.9124{col 52}0.362{col 60}-.058086{col 73} .021183
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01478{col 33} .02022{col 43}-0.7307{col 52}0.465{col 60}-.054411{col 73} .024859
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01478{col 33} .02167{col 43}-0.6817{col 52}0.495{col 60}-.057256{col 73} .027704
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      162{col 34}      191{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.085{col 34}    0.085
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      207{col 34}      264

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01742{col 33} .02011{col 43}-0.8661{col 52}0.386{col 60}-.056836{col 73} .021998
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01349{col 33} .02011{col 43}-0.6707{col 52}0.502{col 60}-.052906{col 73} .025928
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01349{col 33} .02157{col 43}-0.6255{col 52}0.532{col 60}-.055757{col 73}  .02878
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      155{col 34}      180{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      198{col 34}      247

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01557{col 33} .02002{col 43}-0.7777{col 52}0.437{col 60}-.054813{col 73} .023671
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01003{col 33} .02002{col 43}-0.5012{col 52}0.616{col 60}-.049277{col 73} .029207
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01003{col 33} .02181{col 43}-0.4602{col 52}0.645{col 60}-.052773{col 73} .032704
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      142{col 34}      167{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.071{col 34}    0.071
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      183{col 34}      226

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01269{col 33} .02006{col 43}-0.6325{col 52}0.527{col 60}-.052017{col 73} .026634
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00492{col 33} .02006{col 43}-0.2454{col 52}0.806{col 60} -.04425{col 73} .034401
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00492{col 33} .02261{col 43}-0.2178{col 52}0.828{col 60} -.04924{col 73} .039392
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      123{col 34}      148{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      169{col 34}      204

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00932{col 33} .02042{col 43}-0.4565{col 52}0.648{col 60}-.049349{col 73} .030703
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00079{col 33} .02042{col 43}-0.0387{col 52}0.969{col 60}-.040817{col 73} .039234
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00079{col 33}  .0237{col 43}-0.0334{col 52}0.973{col 60}-.047249{col 73} .045666
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      108{col 34}      131{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.693{col 34}    0.693
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      160{col 34}      187

Outcome: fruns_any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00583{col 33} .02081{col 43}-0.2800{col 52}0.779{col 60}-.046614{col 73}  .03496
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00134{col 33} .02081{col 43}0.0646{col 52}0.948{col 60}-.039443{col 73} .042131
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00134{col 33} .02414{col 43}0.0557{col 52}0.956{col 60}-.045972{col 73}  .04866
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 27
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 27.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E2_fruns_any.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}. 
.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         ******************
.         *       FIGURES TABLE 3
.         ******************
.         **Here is where the running variable goes.
.         foreach x in margin_victory {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in $outcomes3 {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_E1_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      327{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      413{col 34}      492

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13972{col 33} .03956{col 43}-3.5318{col 52}0.000{col 60}-.217256{col 73}-.062182
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15305{col 33} .03956{col 43}-3.8687{col 52}0.000{col 60}-.230584{col 73} -.07551
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15305{col 33} .04489{col 43}-3.4091{col 52}0.001{col 60}-.241036{col 73}-.065058
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      436{col 34}      514{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.144{col 34}    0.144
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.263{col 34}    0.263
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      513{col 34}      620

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10078{col 33} .02946{col 43}-3.4212{col 52}0.001{col 60}-.158513{col 73}-.043044
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10432{col 33} .02946{col 43}-3.5416{col 52}0.000{col 60}-.162059{col 73}-.046589
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10432{col 33} .03468{col 43}-3.0079{col 52}0.003{col 60}-.172302{col 73}-.036346
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      501{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.139{col 34}    0.139
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.254{col 34}    0.254
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      510{col 34}      618

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10207{col 33}  .0299{col 43}-3.4132{col 52}0.001{col 60}-.160676{col 73}-.043457
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10604{col 33}  .0299{col 43}-3.5462{col 52}0.000{col 60}-.164655{col 73}-.047435
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10604{col 33} .03519{col 43}-3.0132{col 52}0.003{col 60}-.175023{col 73}-.037067
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      418{col 34}      497{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.244{col 34}    0.244
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      510{col 34}      613

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10403{col 33} .03036{col 43}-3.4261{col 52}0.001{col 60}-.163537{col 73}-.044516
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10834{col 33} .03036{col 43}-3.5683{col 52}0.000{col 60}-.167854{col 73}-.048833
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10834{col 33}  .0357{col 43}-3.0352{col 52}0.002{col 60}-.178304{col 73}-.038382
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      411{col 34}      489{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.235{col 34}    0.235
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      506{col 34}      607

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10658{col 33} .03088{col 43}-3.4513{col 52}0.001{col 60}-.167104{col 73}-.046053
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11126{col 33} .03088{col 43}-3.6030{col 52}0.000{col 60}-.171789{col 73}-.050738
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11126{col 33} .03629{col 43}-3.0660{col 52}0.002{col 60} -.18239{col 73}-.040137
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      404{col 34}      472{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.226{col 34}    0.226
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      504{col 34}      604

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10828{col 33}  .0315{col 43}-3.4374{col 52}0.001{col 60}-.170015{col 73} -.04654
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11327{col 33}  .0315{col 43}-3.5959{col 52}0.000{col 60}-.175007{col 73}-.051532
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11327{col 33} .03688{col 43}-3.0716{col 52}0.002{col 60}-.185545{col 73}-.040994
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      392{col 34}      456{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.217{col 34}    0.217
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      499{col 34}      599

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10989{col 33} .03213{col 43}-3.4199{col 52}0.001{col 60}-.172868{col 73}-.046912
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11542{col 33} .03213{col 43}-3.5922{col 52}0.000{col 60}-.178403{col 73}-.052447
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11542{col 33} .03738{col 43}-3.0878{col 52}0.002{col 60}-.188691{col 73}-.042159
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      381{col 34}      445{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.208{col 34}    0.208
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      498{col 34}      598

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11219{col 33} .03281{col 43}-3.4192{col 52}0.001{col 60}-.176494{col 73}-.047879
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11833{col 33} .03281{col 43}-3.6063{col 52}0.000{col 60}-.182633{col 73}-.054017
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11833{col 33} .03791{col 43}-3.1212{col 52}0.002{col 60}-.192628{col 73}-.044022
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      367{col 34}      433{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.199{col 34}    0.199
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      494{col 34}      593

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11517{col 33} .03352{col 43}-3.4356{col 52}0.001{col 60}-.180866{col 73}-.049466
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12187{col 33} .03352{col 43}-3.6357{col 52}0.000{col 60}-.187572{col 73}-.056172
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12187{col 33} .03849{col 43}-3.1660{col 52}0.002{col 60}-.197318{col 73}-.046426
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      353{col 34}      418{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.190{col 34}    0.190
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      491{col 34}      588

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11792{col 33} .03412{col 43}-3.4561{col 52}0.001{col 60}-.184785{col 73}-.051046
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12484{col 33} .03412{col 43}-3.6590{col 52}0.000{col 60}-.191707{col 73}-.057968
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12484{col 33} .03898{col 43}-3.2022{col 52}0.001{col 60}-.201245{col 73}-.048429
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      344{col 34}      409{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.181{col 34}    0.181
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      486{col 34}      578

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.12096{col 33} .03468{col 43}-3.4881{col 52}0.000{col 60}-.188922{col 73}-.052991
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12861{col 33} .03468{col 43}-3.7088{col 52}0.000{col 60}-.196574{col 73}-.060643
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12861{col 33} .03954{col 43}-3.2530{col 52}0.001{col 60}-.206097{col 73}-.051121
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      334{col 34}      391{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.171{col 34}    0.171
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      481{col 34}      569

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1248{col 33} .03525{col 43}-3.5409{col 52}0.000{col 60}-.193883{col 73}-.055721
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1335{col 33} .03525{col 43}-3.7877{col 52}0.000{col 60}-.202583{col 73} -.06442
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1335{col 33} .04013{col 43}-3.3267{col 52}0.001{col 60}-.212154{col 73}-.054849
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      331{col 34}      385{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.162{col 34}    0.162
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      473{col 34}      555

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.12814{col 33} .03589{col 43}-3.5702{col 52}0.000{col 60}-.198484{col 73}-.057793
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13839{col 33} .03589{col 43}-3.8559{col 52}0.000{col 60}-.208738{col 73}-.068046
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13839{col 33}  .0409{col 43}-3.3836{col 52}0.001{col 60}-.218557{col 73}-.058227
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      320{col 34}      375{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.153{col 34}    0.153
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      457{col 34}      537

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13052{col 33} .03675{col 43}-3.5514{col 52}0.000{col 60} -.20255{col 73}-.058489
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1426{col 33} .03675{col 43}-3.8801{col 52}0.000{col 60}-.214628{col 73}-.070566
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1426{col 33} .04189{col 43}-3.4038{col 52}0.001{col 60}-.224707{col 73}-.060487
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      308{col 34}      360{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.144{col 34}    0.144
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      438{col 34}      516

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13393{col 33} .03771{col 43}-3.5512{col 52}0.000{col 60}-.207848{col 73}-.060011
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.14781{col 33} .03771{col 43}-3.9192{col 52}0.000{col 60}-.221729{col 73}-.073892
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.14781{col 33} .04307{col 43}-3.4321{col 52}0.001{col 60}-.232222{col 73}  -.0634
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      292{col 34}      338{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.135{col 34}    0.135
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      419{col 34}      497

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1381{col 33} .03897{col 43}-3.5440{col 52}0.000{col 60}-.214476{col 73}-.061727
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15195{col 33} .03897{col 43}-3.8993{col 52}0.000{col 60}-.228321{col 73}-.075572
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15195{col 33} .04431{col 43}-3.4294{col 52}0.001{col 60}-.238786{col 73}-.065108
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      311{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.126{col 34}    0.126
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      408{col 34}      480

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1412{col 33} .04024{col 43}-3.5085{col 52}0.000{col 60}-.220074{col 73}-.062319
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15471{col 33} .04024{col 43}-3.8441{col 52}0.000{col 60}-.233583{col 73}-.075828
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15471{col 33} .04566{col 43}-3.3879{col 52}0.001{col 60}-.244205{col 73}-.065205
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      257{col 34}      293{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      386{col 34}      450

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14155{col 33} .04133{col 43}-3.4251{col 52}0.001{col 60}-.222556{col 73}-.060551
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15646{col 33} .04133{col 43}-3.7858{col 52}0.000{col 60}-.237467{col 73}-.075461
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15646{col 33} .04714{col 43}-3.3194{col 52}0.001{col 60}-.248851{col 73}-.064078
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      243{col 34}      272{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      360{col 34}      427

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14068{col 33} .04239{col 43}-3.3184{col 52}0.001{col 60}-.223766{col 73} -.05759
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15578{col 33} .04239{col 43}-3.6747{col 52}0.000{col 60}-.238868{col 73}-.072692
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15578{col 33} .04884{col 43}-3.1898{col 52}0.001{col 60}  -.2515{col 73} -.06006
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      231{col 34}      260{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      344{col 34}      409

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14096{col 33} .04374{col 43}-3.2229{col 52}0.001{col 60}-.226684{col 73}-.055238
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15488{col 33} .04374{col 43}-3.5411{col 52}0.000{col 60}-.240599{col 73}-.069153
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15488{col 33}  .0504{col 43}-3.0732{col 52}0.002{col 60} -.25365{col 73}-.056102
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      213{col 34}      242{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      331{col 34}      386

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14457{col 33} .04561{col 43}-3.1698{col 52}0.002{col 60}-.233955{col 73}-.055179
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15447{col 33} .04561{col 43}-3.3869{col 52}0.001{col 60}-.243855{col 73}-.065079
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15447{col 33} .05179{col 43}-2.9825{col 52}0.003{col 60}-.255978{col 73}-.052957
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      184{col 34}      215{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.080{col 34}    0.080
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      310{col 34}      363

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15184{col 33}  .0477{col 43}-3.1832{col 52}0.001{col 60}-.245333{col 73}-.058348
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15956{col 33}  .0477{col 43}-3.3450{col 52}0.001{col 60}-.253054{col 73}-.066069
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15956{col 33} .05337{col 43}-2.9899{col 52}0.003{col 60}-.264159{col 73}-.054965
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      161{col 34}      188{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.071{col 34}    0.071
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      280{col 34}      323

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16216{col 33} .04953{col 43}-3.2737{col 52}0.001{col 60} -.25925{col 73}-.065077
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.16582{col 33} .04953{col 43}-3.3475{col 52}0.001{col 60}-.262903{col 73} -.06873
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.16582{col 33} .05483{col 43}-3.0244{col 52}0.002{col 60}-.273273{col 73} -.05836
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      137{col 34}      165{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.062{col 34}    0.062
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.548{col 34}    0.548
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      251{col 34}      286

Outcome: donate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16847{col 33} .05152{col 43}-3.2702{col 52}0.001{col 60}-.269435{col 73}-.067498
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17174{col 33} .05152{col 43}-3.3337{col 52}0.001{col 60}-.272706{col 73}-.070769
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17174{col 33} .05643{col 43}-3.0436{col 52}0.002{col 60}-.282329{col 73}-.061146
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 24
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 24.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E1_donate_15any.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      306{col 34}      357{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      443{col 34}      520

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11359{col 33} .03363{col 43}-3.3771{col 52}0.001{col 60}-.179511{col 73}-.047665
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12538{col 33} .03363{col 43}-3.7276{col 52}0.000{col 60}-.191298{col 73}-.059452
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12538{col 33} .03833{col 43}-3.2711{col 52}0.001{col 60}-.200497{col 73}-.050253
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      459{col 34}      539{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.154{col 34}    0.154
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.292{col 34}    0.292
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      516{col 34}      624

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07956{col 33} .02453{col 43}-3.2434{col 52}0.001{col 60} -.12764{col 73}-.031483
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08174{col 33} .02453{col 43}-3.3323{col 52}0.001{col 60}-.129821{col 73}-.033664
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08174{col 33} .02885{col 43}-2.8335{col 52}0.005{col 60}-.138285{col 73}  -.0252
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      448{col 34}      528{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.149{col 34}    0.149
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.282{col 34}    0.282
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      515{col 34}      623

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07963{col 33} .02493{col 43}-3.1938{col 52}0.001{col 60}-.128502{col 73}-.030765
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08171{col 33} .02493{col 43}-3.2770{col 52}0.001{col 60}-.130576{col 73}-.032838
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08171{col 33} .02922{col 43}-2.7960{col 52}0.005{col 60}-.138983{col 73}-.024431
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      436{col 34}      514{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.144{col 34}    0.144
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.273{col 34}    0.273
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      514{col 34}      622

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08003{col 33} .02533{col 43}-3.1598{col 52}0.002{col 60}-.129678{col 73} -.03039
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08194{col 33} .02533{col 43}-3.2350{col 52}0.001{col 60}-.131584{col 73}-.032297
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08194{col 33} .02962{col 43}-2.7664{col 52}0.006{col 60}-.139995{col 73}-.023886
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      501{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.139{col 34}    0.139
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.263{col 34}    0.263
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      513{col 34}      620

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08098{col 33} .02572{col 43}-3.1489{col 52}0.002{col 60}-.131384{col 73}-.030576
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08279{col 33} .02572{col 43}-3.2192{col 52}0.001{col 60}-.133191{col 73}-.032383
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08279{col 33} .03004{col 43}-2.7561{col 52}0.006{col 60} -.14166{col 73}-.023914
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      418{col 34}      497{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.254{col 34}    0.254
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      510{col 34}      618

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08255{col 33} .02611{col 43}-3.1612{col 52}0.002{col 60}-.133737{col 73}-.031369
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08446{col 33} .02611{col 43}-3.2343{col 52}0.001{col 60}-.135648{col 73} -.03328
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08446{col 33} .03051{col 43}-2.7687{col 52}0.006{col 60}-.144256{col 73}-.024671
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      411{col 34}      489{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.244{col 34}    0.244
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      510{col 34}      613

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08475{col 33} .02656{col 43}-3.1911{col 52}0.001{col 60}-.136807{col 73}-.032698
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08669{col 33} .02656{col 43}-3.2642{col 52}0.001{col 60}-.138748{col 73}-.034639
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08669{col 33} .03099{col 43}-2.7978{col 52}0.005{col 60}-.147425{col 73}-.025963
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      404{col 34}      472{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.235{col 34}    0.235
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      506{col 34}      607

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08668{col 33}  .0271{col 43}-3.1991{col 52}0.001{col 60}-.139788{col 73}-.033575
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08877{col 33}  .0271{col 43}-3.2760{col 52}0.001{col 60}-.141873{col 73} -.03566
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08877{col 33} .03156{col 43}-2.8125{col 52}0.005{col 60}-.150625{col 73}-.026908
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      392{col 34}      456{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.119{col 34}    0.119
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.225{col 34}    0.225
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      504{col 34}      604

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08866{col 33} .02766{col 43}-3.2055{col 52}0.001{col 60}-.142869{col 73} -.03445
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09116{col 33} .02766{col 43}-3.2961{col 52}0.001{col 60}-.145374{col 73}-.036955
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09116{col 33} .03211{col 43}-2.8391{col 52}0.005{col 60}-.154099{col 73}-.028229
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      381{col 34}      445{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.216{col 34}    0.216
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      499{col 34}      599

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09139{col 33} .02827{col 43}-3.2321{col 52}0.001{col 60}-.146803{col 73}-.035968
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09436{col 33} .02827{col 43}-3.3374{col 52}0.001{col 60}-.149781{col 73}-.038946
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09436{col 33}  .0326{col 43}-2.8944{col 52}0.004{col 60}-.158263{col 73}-.030464
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      367{col 34}      433{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.206{col 34}    0.206
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      498{col 34}      598

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09476{col 33} .02893{col 43}-3.2748{col 52}0.001{col 60}-.151467{col 73}-.038045
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09833{col 33} .02893{col 43}-3.3983{col 52}0.001{col 60} -.15504{col 73}-.041617
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09833{col 33} .03315{col 43}-2.9662{col 52}0.003{col 60}-.163299{col 73}-.033357
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      353{col 34}      418{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.197{col 34}    0.197
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      492{col 34}      591

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09765{col 33} .02952{col 43}-3.3083{col 52}0.001{col 60}-.155507{col 73}  -.0398
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10182{col 33} .02952{col 43}-3.4495{col 52}0.001{col 60}-.159675{col 73}-.043968
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10182{col 33} .03371{col 43}-3.0209{col 52}0.003{col 60}-.167884{col 73}-.035759
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      344{col 34}      409{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.187{col 34}    0.187
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      491{col 34}      587

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10066{col 33} .03009{col 43}-3.3457{col 52}0.001{col 60}-.159626{col 73}-.041692
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1053{col 33} .03009{col 43}-3.4998{col 52}0.000{col 60}-.164262{col 73}-.046328
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1053{col 33} .03425{col 43}-3.0744{col 52}0.002{col 60}-.172422{col 73}-.038168
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      334{col 34}      391{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.178{col 34}    0.178
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      484{col 34}      574

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10432{col 33} .03069{col 43}-3.3994{col 52}0.001{col 60}-.164465{col 73}-.044172
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10981{col 33} .03069{col 43}-3.5782{col 52}0.000{col 60}-.169955{col 73}-.049661
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10981{col 33}  .0349{col 43}-3.1464{col 52}0.002{col 60}-.178211{col 73}-.041405
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      331{col 34}      385{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.169{col 34}    0.169
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      480{col 34}      568

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10722{col 33} .03138{col 43}-3.4171{col 52}0.001{col 60}-.168719{col 73}-.045721
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1141{col 33} .03138{col 43}-3.6365{col 52}0.000{col 60}-.175602{col 73}-.052605
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1141{col 33} .03569{col 43}-3.1970{col 52}0.001{col 60}-.184056{col 73}-.044151
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      320{col 34}      375{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.159{col 34}    0.159
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      465{col 34}      544

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11017{col 33} .03226{col 43}-3.4148{col 52}0.001{col 60}-.173406{col 73}-.046938
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11884{col 33} .03226{col 43}-3.6835{col 52}0.000{col 60}-.182074{col 73}-.055606
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11884{col 33}  .0367{col 43}-3.2378{col 52}0.001{col 60}-.190778{col 73}-.046902
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      308{col 34}      360{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.150{col 34}    0.150
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      449{col 34}      529

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11275{col 33} .03326{col 43}-3.3905{col 52}0.001{col 60}-.177932{col 73}-.047573
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12389{col 33} .03326{col 43}-3.7253{col 52}0.000{col 60}-.189066{col 73}-.058708
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12389{col 33}  .0379{col 43}-3.2686{col 52}0.001{col 60}-.198172{col 73}-.049601
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      292{col 34}      338{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.140{col 34}    0.140
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      428{col 34}      504

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11567{col 33} .03453{col 43}-3.3500{col 52}0.001{col 60}-.183337{col 73}-.047995
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1284{col 33} .03453{col 43}-3.7189{col 52}0.000{col 60}-.196074{col 73}-.060732
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1284{col 33} .03926{col 43}-3.2704{col 52}0.001{col 60}-.205355{col 73} -.05145
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      311{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      413{col 34}      492

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11856{col 33} .03581{col 43}-3.3104{col 52}0.001{col 60}-.188757{col 73}-.048365
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13123{col 33} .03581{col 43}-3.6641{col 52}0.000{col 60}-.201424{col 73}-.061033
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13123{col 33} .04057{col 43}-3.2346{col 52}0.001{col 60}-.210745{col 73}-.051712
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      257{col 34}      293{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.121{col 34}    0.121
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      395{col 34}      462

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11866{col 33} .03692{col 43}-3.2140{col 52}0.001{col 60}-.191027{col 73}  -.0463
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13232{col 33} .03692{col 43}-3.5838{col 52}0.000{col 60} -.20468{col 73}-.059953
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13232{col 33} .04195{col 43}-3.1538{col 52}0.002{col 60}-.214546{col 73}-.050086
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      243{col 34}      272{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.112{col 34}    0.112
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      375{col 34}      441

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11715{col 33} .03802{col 43}-3.0814{col 52}0.002{col 60}-.191666{col 73}-.042635
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  -.131{col 33} .03802{col 43}-3.4457{col 52}0.001{col 60}-.205518{col 73}-.056487
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  -.131{col 33} .04351{col 43}-3.0111{col 52}0.003{col 60}-.216274{col 73} -.04573
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      231{col 34}      260{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      351{col 34}      416

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11609{col 33}  .0394{col 43}-2.9462{col 52}0.003{col 60}-.193327{col 73}-.038863
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12866{col 33}  .0394{col 43}-3.2652{col 52}0.001{col 60}-.205896{col 73}-.051432
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12866{col 33}  .0452{col 43}-2.8465{col 52}0.004{col 60}-.217255{col 73}-.040073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      213{col 34}      242{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      333{col 34}      391

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11694{col 33} .04125{col 43}-2.8350{col 52}0.005{col 60}-.197783{col 73}-.036094
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12593{col 33} .04125{col 43}-3.0530{col 52}0.002{col 60}-.206774{col 73}-.045085
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12593{col 33} .04667{col 43}-2.6985{col 52}0.007{col 60}-.217393{col 73}-.034466
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      184{col 34}      215{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      316{col 34}      369

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.12417{col 33} .04318{col 43}-2.8758{col 52}0.004{col 60}  -.2088{col 73}-.039543
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13006{col 33} .04318{col 43}-3.0123{col 52}0.003{col 60}-.214693{col 73}-.045436
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13006{col 33} .04798{col 43}-2.7110{col 52}0.007{col 60}-.224096{col 73}-.036033
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      161{col 34}      188{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      292{col 34}      338

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13572{col 33} .04477{col 43}-3.0318{col 52}0.002{col 60}-.223465{col 73}-.047984
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13896{col 33} .04477{col 43}-3.1042{col 52}0.002{col 60}-.226702{col 73}-.051221
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13896{col 33} .04889{col 43}-2.8424{col 52}0.004{col 60}-.234783{col 73} -.04314
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1150
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      518{col 34}      632{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      137{col 34}      165{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.528{col 34}    0.528
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      258{col 34}      293

Outcome: b5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14193{col 33} .04647{col 43}-3.0542{col 52}0.002{col 60}-.233009{col 73} -.05085
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.14243{col 33} .04647{col 43}-3.0649{col 52}0.002{col 60}-.233507{col 73}-.051348
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.14243{col 33} .05008{col 43}-2.8438{col 52}0.004{col 60}-.240589{col 73}-.044266
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 26
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 26.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E1_b5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
. 
.         
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         **Here is where the running variable goes.
.         foreach x in margin_victory {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in $outcomes5 {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_E3_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      245{col 34}      287{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      404

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05392{col 33} .04088{col 43}-1.3189{col 52}0.187{col 60}-.134041{col 73} .026207
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05926{col 33} .04088{col 43}-1.4497{col 52}0.147{col 60}-.139389{col 73}  .02086
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05926{col 33}  .0481{col 43}-1.2320{col 52}0.218{col 60}-.153548{col 73} .035019
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      354{col 34}      425{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.208{col 34}    0.208
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.346{col 34}    0.346
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      371{col 34}      450

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04677{col 33} .03078{col 43}-1.5194{col 52}0.129{col 60}-.107092{col 73} .013561
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0338{col 33} .03078{col 43}-1.0980{col 52}0.272{col 60}-.094124{col 73} .026529
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0338{col 33}  .0376{col 43}-0.8989{col 52}0.369{col 60}-.107485{col 73} .039891
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      354{col 34}      424{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.203{col 34}    0.203
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.338{col 34}    0.338
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      371{col 34}      450

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0457{col 33} .03096{col 43}-1.4762{col 52}0.140{col 60}-.106384{col 73} .014977
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03281{col 33} .03096{col 43}-1.0596{col 52}0.289{col 60}-.093486{col 73} .027875
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03281{col 33} .03784{col 43}-0.8671{col 52}0.386{col 60}-.106961{col 73}  .04135
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      350{col 34}      422{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.198{col 34}    0.198
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.329{col 34}    0.329
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      371{col 34}      450

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04469{col 33} .03115{col 43}-1.4345{col 52}0.151{col 60}-.105749{col 73}  .01637
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03182{col 33} .03115{col 43}-1.0215{col 52}0.307{col 60}-.092883{col 73} .029236
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03182{col 33}  .0381{col 43}-0.8352{col 52}0.404{col 60}-.106504{col 73} .042857
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      349{col 34}      420{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.193{col 34}    0.193
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.321{col 34}    0.321
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      370{col 34}      449

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04371{col 33} .03136{col 43}-1.3942{col 52}0.163{col 60} -.10517{col 73} .017741
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03086{col 33} .03136{col 43}-0.9841{col 52}0.325{col 60}-.092313{col 73} .030599
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03086{col 33} .03839{col 43}-0.8038{col 52}0.421{col 60}-.106095{col 73} .044381
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      349{col 34}      418{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.188{col 34}    0.188
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.313{col 34}    0.313
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      370{col 34}      449

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04257{col 33}  .0316{col 43}-1.3474{col 52}0.178{col 60}-.104495{col 73} .019355
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0298{col 33}  .0316{col 43}-0.9433{col 52}0.346{col 60}-.091729{col 73} .032122
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0298{col 33} .03865{col 43}-0.7712{col 52}0.441{col 60} -.10555{col 73} .045943
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      347{col 34}      414{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.183{col 34}    0.183
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.304{col 34}    0.304
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      370{col 34}      448

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04121{col 33} .03188{col 43}-1.2928{col 52}0.196{col 60}-.103695{col 73}  .02127
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02855{col 33} .03188{col 43}-0.8957{col 52}0.370{col 60}-.091036{col 73} .033928
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02855{col 33} .03896{col 43}-0.7329{col 52}0.464{col 60}-.104909{col 73} .047802
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      342{col 34}      407{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.178{col 34}    0.178
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.296{col 34}    0.296
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      370{col 34}      447

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03989{col 33} .03217{col 43}-1.2398{col 52}0.215{col 60}-.102952{col 73}  .02317
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02745{col 33} .03217{col 43}-0.8533{col 52}0.393{col 60}-.090516{col 73} .035606
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02745{col 33} .03931{col 43}-0.6984{col 52}0.485{col 60}  -.1045{col 73}  .04959
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      341{col 34}      404{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.288{col 34}    0.288
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      370{col 34}      447

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03855{col 33} .03251{col 43}-1.1856{col 52}0.236{col 60}-.102266{col 73} .025175
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02634{col 33} .03251{col 43}-0.8103{col 52}0.418{col 60}-.090064{col 73} .037378
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02634{col 33} .03974{col 43}-0.6629{col 52}0.507{col 60}-.104226{col 73} .051541
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      402{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.168{col 34}    0.168
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.280{col 34}    0.280
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      369{col 34}      446

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03733{col 33} .03293{col 43}-1.1337{col 52}0.257{col 60}-.101873{col 73}  .02721
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02541{col 33} .03293{col 43}-0.7717{col 52}0.440{col 60}-.089953{col 73} .039131
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02541{col 33} .04019{col 43}-0.6323{col 52}0.527{col 60}-.104182{col 73}  .05336
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      334{col 34}      390{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.163{col 34}    0.163
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.271{col 34}    0.271
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      368{col 34}      445

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03605{col 33} .03338{col 43}-1.0803{col 52}0.280{col 60}-.101468{col 73} .029361
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0244{col 33} .03338{col 43}-0.7310{col 52}0.465{col 60}-.089812{col 73} .041016
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0244{col 33}  .0407{col 43}-0.5995{col 52}0.549{col 60}-.104161{col 73} .055365
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      325{col 34}      382{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.158{col 34}    0.158
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.263{col 34}    0.263
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      367{col 34}      443

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03499{col 33} .03387{col 43}-1.0331{col 52}0.302{col 60} -.10137{col 73} .031391
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02367{col 33} .03387{col 43}-0.6988{col 52}0.485{col 60}-.090046{col 73} .042715
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02367{col 33} .04124{col 43}-0.5739{col 52}0.566{col 60}-.104487{col 73} .057156
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      320{col 34}      377{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.153{col 34}    0.153
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.255{col 34}    0.255
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      366{col 34}      442

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03417{col 33}  .0344{col 43}-0.9934{col 52}0.321{col 60}-.101585{col 73} .033246
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02315{col 33}  .0344{col 43}-0.6730{col 52}0.501{col 60}-.090564{col 73} .044267
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02315{col 33} .04186{col 43}-0.5530{col 52}0.580{col 60}-.105186{col 73}  .05889
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      312{col 34}      370{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.246{col 34}    0.246
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      365{col 34}      438

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03385{col 33} .03499{col 43}-0.9673{col 52}0.333{col 60} -.10243{col 73} .034736
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02336{col 33} .03499{col 43}-0.6675{col 52}0.504{col 60} -.09194{col 73} .045226
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02336{col 33} .04247{col 43}-0.5499{col 52}0.582{col 60}-.106606{col 73} .059892
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      303{col 34}      359{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.238{col 34}    0.238
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      363{col 34}      434

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03403{col 33} .03557{col 43}-0.9567{col 52}0.339{col 60}-.103745{col 73} .035688
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02401{col 33} .03557{col 43}-0.6751{col 52}0.500{col 60} -.09373{col 73} .045702
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02401{col 33}  .0432{col 43}-0.5559{col 52}0.578{col 60}-.108682{col 73} .060654
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      295{col 34}      351{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.230{col 34}    0.230
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      360{col 34}      432

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03462{col 33} .03614{col 43}-0.9580{col 52}0.338{col 60}-.105459{col 73} .036214
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02499{col 33} .03614{col 43}-0.6916{col 52}0.489{col 60}-.095831{col 73} .045841
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02499{col 33} .04386{col 43}-0.5699{col 52}0.569{col 60}-.110959{col 73} .060969
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      289{col 34}      348{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.221{col 34}    0.221
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      356{col 34}      428

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0367{col 33} .03673{col 43}-0.9992{col 52}0.318{col 60}-.108679{col 73} .035286
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0283{col 33} .03673{col 43}-0.7707{col 52}0.441{col 60}-.100286{col 73} .043679
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0283{col 33} .04445{col 43}-0.6368{col 52}0.524{col 60}-.115419{col 73} .058812
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      283{col 34}      342{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.213{col 34}    0.213
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      355{col 34}      426

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03926{col 33} .03738{col 43}-1.0504{col 52}0.294{col 60}-.112516{col 73} .033997
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03266{col 33} .03738{col 43}-0.8737{col 52}0.382{col 60}-.105912{col 73} .040601
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03266{col 33} .04499{col 43}-0.7259{col 52}0.468{col 60}-.120832{col 73} .055521
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      278{col 34}      323{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.123{col 34}    0.123
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.205{col 34}    0.205
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      354{col 34}      424

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04082{col 33} .03811{col 43}-1.0712{col 52}0.284{col 60}-.115506{col 73} .033866
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03623{col 33} .03811{col 43}-0.9508{col 52}0.342{col 60}-.110918{col 73} .038454
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03623{col 33} .04561{col 43}-0.7944{col 52}0.427{col 60}-.125627{col 73} .053164
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      317{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.118{col 34}    0.118
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.196{col 34}    0.196
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      350{col 34}      421

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04287{col 33} .03889{col 43}-1.1023{col 52}0.270{col 60}-.119085{col 73} .033351
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04041{col 33} .03889{col 43}-1.0391{col 52}0.299{col 60}-.116625{col 73} .035811
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04041{col 33} .04625{col 43}-0.8737{col 52}0.382{col 60}-.131056{col 73} .050242
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      310{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.188{col 34}    0.188
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      349{col 34}      418

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04605{col 33}  .0397{col 43}-1.1597{col 52}0.246{col 60}-.123863{col 73} .031773
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04589{col 33}  .0397{col 43}-1.1559{col 52}0.248{col 60}-.123711{col 73} .031925
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04589{col 33} .04689{col 43}-0.9787{col 52}0.328{col 60}-.137801{col 73} .046015
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      249{col 34}      296{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.180{col 34}    0.180
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      343{col 34}      408

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05076{col 33} .04044{col 43}-1.2553{col 52}0.209{col 60} -.13001{col 73} .028493
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05348{col 33} .04044{col 43}-1.3227{col 52}0.186{col 60}-.132735{col 73} .025768
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05348{col 33} .04759{col 43}-1.1238{col 52}0.261{col 60}-.146764{col 73} .039797
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      244{col 34}      286{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.171{col 34}    0.171
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      403

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05466{col 33} .04098{col 43}-1.3339{col 52}0.182{col 60}-.134973{col 73} .025655
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0606{col 33} .04098{col 43}-1.4789{col 52}0.139{col 60}-.140914{col 73} .019714
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0606{col 33} .04824{col 43}-1.2563{col 52}0.209{col 60}-.155144{col 73} .033944
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      240{col 34}      280{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.098{col 34}    0.098
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.163{col 34}    0.163
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      334{col 34}      390

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0595{col 33} .04156{col 43}-1.4319{col 52}0.152{col 60}-.140953{col 73} .021946
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06936{col 33} .04156{col 43}-1.6691{col 52}0.095{col 60}-.150811{col 73} .012088
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06936{col 33} .04909{col 43}-1.4130{col 52}0.158{col 60}-.165572{col 73}  .02685
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      235{col 34}      266{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.155{col 34}    0.155
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      322{col 34}      380

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06478{col 33} .04219{col 43}-1.5351{col 52}0.125{col 60}-.147476{col 73} .017925
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07896{col 33} .04219{col 43}-1.8713{col 52}0.061{col 60}-.161659{col 73} .003742
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07896{col 33}  .0501{col 43}-1.5760{col 52}0.115{col 60}-.177154{col 73} .019237
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      233{col 34}      262{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.146{col 34}    0.146
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      309{col 34}      368

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07007{col 33} .04306{col 43}-1.6273{col 52}0.104{col 60}-.154458{col 73} .014326
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08912{col 33} .04306{col 43}-2.0697{col 52}0.038{col 60}-.173508{col 73}-.004725
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08912{col 33} .05148{col 43}-1.7311{col 52}0.083{col 60}-.190014{col 73} .011781
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      224{col 34}      250{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      295{col 34}      351

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07307{col 33} .04428{col 43}-1.6501{col 52}0.099{col 60}-.159862{col 73} .013721
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09603{col 33} .04428{col 43}-2.1685{col 52}0.030{col 60}-.182818{col 73}-.009235
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09603{col 33} .05307{col 43}-1.8093{col 52}0.070{col 60}-.200047{col 73} .007994
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      243{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.130{col 34}    0.130
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      285{col 34}      344

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07738{col 33} .04581{col 43}-1.6890{col 52}0.091{col 60}-.167162{col 73} .012411
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10108{col 33} .04581{col 43}-2.2066{col 52}0.027{col 60} -.19087{col 73}-.011297
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10108{col 33} .05493{col 43}-1.8402{col 52}0.066{col 60}-.208748{col 73} .006581
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      202{col 34}      226{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.121{col 34}    0.121
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      276{col 34}      321

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08342{col 33} .04791{col 43}-1.7413{col 52}0.082{col 60}-.177315{col 73} .010474
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11014{col 33} .04791{col 43}-2.2990{col 52}0.022{col 60}-.204033{col 73}-.016244
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11014{col 33} .05738{col 43}-1.9195{col 52}0.055{col 60}-.222596{col 73} .002319
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      184{col 34}      205{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      264{col 34}      310

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08816{col 33} .05004{col 43}-1.7618{col 52}0.078{col 60}-.186248{col 73} .009919
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11784{col 33} .05004{col 43}-2.3548{col 52}0.019{col 60}-.215923{col 73}-.019757
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11784{col 33} .06042{col 43}-1.9503{col 52}0.051{col 60}-.236263{col 73} .000583
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      171{col 34}      191{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      290

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09168{col 33} .05207{col 43}-1.7608{col 52}0.078{col 60}-.193733{col 73} .010368
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12085{col 33} .05207{col 43}-2.3210{col 52}0.020{col 60}-.222899{col 73}-.018798
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12085{col 33} .06334{col 43}-1.9078{col 52}0.056{col 60}   -.245{col 73} .003303
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      163{col 34}      181{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      240{col 34}      277

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09445{col 33} .05412{col 43}-1.7451{col 52}0.081{col 60}-.200533{col 73} .011631
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12066{col 33} .05412{col 43}-2.2292{col 52}0.026{col 60}-.226737{col 73}-.014573
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12066{col 33} .06567{col 43}-1.8373{col 52}0.066{col 60}-.249367{col 73} .008057
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      153{col 34}      169{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      234{col 34}      263

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09863{col 33} .05663{col 43}-1.7418{col 52}0.082{col 60}-.209613{col 73} .012353
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.11944{col 33} .05663{col 43}-2.1092{col 52}0.035{col 60}-.230419{col 73}-.008453
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.11944{col 33} .06813{col 43}-1.7530{col 52}0.080{col 60}-.252973{col 73}   .0141
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      139{col 34}      158{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.080{col 34}    0.080
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.601{col 34}    0.601
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      218{col 34}      247

Outcome: nfdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.11001{col 33} .06062{col 43}-1.8148{col 52}0.070{col 60} -.22883{col 73} .008802
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13089{col 33} .06062{col 43}-2.1591{col 52}0.031{col 60}-.249704{col 73}-.012072
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13089{col 33} .07176{col 43}-1.8240{col 52}0.068{col 60}-.271533{col 73} .009757
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 34
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 34.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E3_nfdonate_15any.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      155{col 34}      175{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.105{col 34}    0.105
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      247{col 34}      291

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07969{col 33} .05297{col 43}-1.5044{col 52}0.132{col 60}-.183502{col 73} .024129
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10016{col 33} .05297{col 43}-1.8909{col 52}0.059{col 60}-.203974{col 73} .003657
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10016{col 33} .06209{col 43}-1.6132{col 52}0.107{col 60}-.221849{col 73} .021531
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      249{col 34}      296{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.209{col 34}    0.209
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      355{col 34}      426

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03538{col 33} .03467{col 43}-1.0205{col 52}0.307{col 60} -.10332{col 73} .032568
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03055{col 33} .03467{col 43}-0.8813{col 52}0.378{col 60}-.098494{col 73} .037394
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03055{col 33} .04017{col 43}-0.7605{col 52}0.447{col 60}-.109288{col 73} .048188
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      244{col 34}      286{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.200{col 34}    0.200
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      352{col 34}      423

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03855{col 33}  .0353{col 43}-1.0920{col 52}0.275{col 60}-.107733{col 73} .030639
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0352{col 33}  .0353{col 43}-0.9973{col 52}0.319{col 60}-.104389{col 73} .033982
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0352{col 33}  .0409{col 43}-0.8607{col 52}0.389{col 60}-.115369{col 73} .044962
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      240{col 34}      280{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.098{col 34}    0.098
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.190{col 34}    0.190
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      349{col 34}      419

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04244{col 33} .03601{col 43}-1.1786{col 52}0.239{col 60}-.113023{col 73} .028135
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04064{col 33} .03601{col 43}-1.1285{col 52}0.259{col 60}-.111216{col 73} .029942
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04064{col 33} .04168{col 43}-0.9750{col 52}0.330{col 60}-.122329{col 73} .041055
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      235{col 34}      266{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.180{col 34}    0.180
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      343{col 34}      409

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04659{col 33} .03684{col 43}-1.2648{col 52}0.206{col 60}-.118791{col 73} .025609
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04707{col 33} .03684{col 43}-1.2777{col 52}0.201{col 60}-.119267{col 73} .025133
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04707{col 33} .04268{col 43}-1.1028{col 52}0.270{col 60}-.130719{col 73} .036585
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      233{col 34}      262{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.171{col 34}    0.171
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      341{col 34}      403

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05043{col 33} .03793{col 43}-1.3294{col 52}0.184{col 60}-.124773{col 73} .023918
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05378{col 33} .03793{col 43}-1.4178{col 52}0.156{col 60}-.128123{col 73} .020567
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05378{col 33} .04393{col 43}-1.2241{col 52}0.221{col 60}-.139887{col 73}  .03233
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      224{col 34}      250{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.161{col 34}    0.161
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      331{col 34}      386

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0542{col 33} .03939{col 43}-1.3758{col 52}0.169{col 60}-.131409{col 73} .023013
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06122{col 33} .03939{col 43}-1.5542{col 52}0.120{col 60}-.138435{col 73} .015986
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06122{col 33} .04564{col 43}-1.3413{col 52}0.180{col 60}-.150686{col 73} .028237
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      243{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.151{col 34}    0.151
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      319{col 34}      375

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05783{col 33} .04122{col 43}-1.4028{col 52}0.161{col 60}-.138619{col 73} .022967
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06901{col 33} .04122{col 43}-1.6740{col 52}0.094{col 60}-.149798{col 73} .011787
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06901{col 33} .04772{col 43}-1.4459{col 52}0.148{col 60}-.162542{col 73} .024531
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      202{col 34}      226{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.141{col 34}    0.141
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      302{col 34}      357

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06348{col 33} .04364{col 43}-1.4547{col 52}0.146{col 60}   -.149{col 73} .022047
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07831{col 33} .04364{col 43}-1.7946{col 52}0.073{col 60}-.163831{col 73} .007216
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07831{col 33} .05034{col 43}-1.5557{col 52}0.120{col 60}-.176964{col 73} .020348
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      184{col 34}      205{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.132{col 34}    0.132
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      288{col 34}      347

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06979{col 33} .04606{col 43}-1.5154{col 52}0.130{col 60}-.160058{col 73} .020476
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08631{col 33} .04606{col 43}-1.8740{col 52}0.061{col 60}-.176574{col 73}  .00396
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08631{col 33} .05293{col 43}-1.6307{col 52}0.103{col 60} -.19004{col 73} .017426
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      171{col 34}      191{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.122{col 34}    0.122
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      277{col 34}      322

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07437{col 33} .04836{col 43}-1.5379{col 52}0.124{col 60}-.169155{col 73}  .02041
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09332{col 33} .04836{col 43}-1.9297{col 52}0.054{col 60}-.188103{col 73} .001462
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09332{col 33} .05573{col 43}-1.6744{col 52}0.094{col 60}-.202559{col 73} .015918
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      163{col 34}      181{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.112{col 34}    0.112
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      262{col 34}      308

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07738{col 33} .05079{col 43}-1.5238{col 52}0.128{col 60}-.176921{col 73} .022153
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09849{col 33} .05079{col 43}-1.9393{col 52}0.052{col 60}-.198024{col 73}  .00105
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09849{col 33} .05927{col 43}-1.6616{col 52}0.097{col 60}-.214661{col 73} .017687
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      153{col 34}      169{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      244{col 34}      286

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08019{col 33} .05377{col 43}-1.4915{col 52}0.136{col 60}-.185576{col 73} .025189
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10045{col 33} .05377{col 43}-1.8683{col 52}0.062{col 60}-.205835{col 73}  .00493
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10045{col 33} .06291{col 43}-1.5968{col 52}0.110{col 60}-.223751{col 73} .022847
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      139{col 34}      158{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      235{col 34}      266

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08937{col 33} .05831{col 43}-1.5326{col 52}0.125{col 60}-.203668{col 73}  .02492
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10641{col 33} .05831{col 43}-1.8247{col 52}0.068{col 60}-.220699{col 73} .007888
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10641{col 33} .06695{col 43}-1.5893{col 52}0.112{col 60}-.237625{col 73} .024814
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      121{col 34}      140{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.043{col 34}    0.043
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      225{col 34}      251

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10486{col 33} .06265{col 43}-1.6737{col 52}0.094{col 60}-.227655{col 73} .017932
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.12006{col 33} .06265{col 43}-1.9163{col 52}0.055{col 60}-.242849{col 73} .002737
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.12006{col 33} .07084{col 43}-1.6947{col 52}0.090{col 60}-.258905{col 73} .018793
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      111{col 34}      124{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.038{col 34}    0.038
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      203{col 34}      228

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.12256{col 33} .06728{col 43}-1.8215{col 52}0.069{col 60}-.254429{col 73} .009316
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13814{col 33} .06728{col 43}-2.0531{col 52}0.040{col 60}-.270009{col 73}-.006264
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13814{col 33} .07549{col 43}-1.8300{col 52}0.067{col 60}-.286087{col 73} .009814
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       96{col 34}      107{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.033{col 34}    0.033
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      176{col 34}      195

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.13272{col 33} .07318{col 43}-1.8138{col 52}0.070{col 60}-.276145{col 73} .010697
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1464{col 33} .07318{col 43}-2.0007{col 52}0.045{col 60}-.289825{col 73}-.002983
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1464{col 33}  .0817{col 43}-1.7919{col 52}0.073{col 60}-.306538{col 73}  .01373
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       87{col 34}       92{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.028{col 34}    0.028
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      155{col 34}      175

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.14368{col 33} .07796{col 43}-1.8431{col 52}0.065{col 60}-.296477{col 73} .009114
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1611{col 33} .07796{col 43}-2.0665{col 52}0.039{col 60}-.313896{col 73}-.008305
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1611{col 33} .08677{col 43}-1.8566{col 52}0.063{col 60}-.331168{col 73} .008966
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       823
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      451{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       75{col 34}       81{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.023{col 34}    0.023
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.045{col 34}    0.045
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.516{col 34}    0.516
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      125{col 34}      145

Outcome: nfb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1624{col 33} .08481{col 43}-1.9149{col 52}0.056{col 60}-.328623{col 73} .003822
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18268{col 33} .08481{col 43}-2.1540{col 52}0.031{col 60}-.348899{col 73}-.016454
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18268{col 33} .09434{col 43}-1.9364{col 52}0.053{col 60}-.367577{col 73} .002225
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 19
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 19.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E3_nfb5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "Data\cand_level_persist_rep.dta",clear
{txt}
{com}.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         **Here is where the running variable goes.
.         foreach x in margin_victory {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in $outcomes4 {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_E3_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      238{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      251{col 34}      306

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.2015{col 33} .05735{col 43}-3.5135{col 52}0.000{col 60}-.313908{col 73}-.089097
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20234{col 33} .05735{col 43}-3.5282{col 52}0.000{col 60}-.314749{col 73}-.089938
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20234{col 33}   .068{col 43}-2.9758{col 52}0.003{col 60}-.335614{col 73}-.069073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      297{col 34}      368{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.222{col 34}    0.222
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      416

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1878{col 33} .04197{col 43}-4.4751{col 52}0.000{col 60} -.27005{col 73}-.105549
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.21101{col 33} .04197{col 43}-5.0282{col 52}0.000{col 60} -.29326{col 73}-.128759
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.21101{col 33} .05232{col 43}-4.0328{col 52}0.000{col 60} -.31356{col 73}-.108458
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      291{col 34}      360{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.214{col 34}    0.214
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1889{col 33} .04254{col 43}-4.4405{col 52}0.000{col 60}-.272276{col 73}-.105521
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.2107{col 33} .04254{col 43}-4.9531{col 52}0.000{col 60}-.294082{col 73}-.127327
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.2107{col 33} .05266{col 43}-4.0016{col 52}0.000{col 60}-.313907{col 73}-.107502
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      283{col 34}      351{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.207{col 34}    0.207
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      413

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19053{col 33}  .0431{col 43}-4.4207{col 52}0.000{col 60}-.275008{col 73}-.106058
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.21106{col 33}  .0431{col 43}-4.8971{col 52}0.000{col 60} -.29554{col 73}-.126589
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.21106{col 33}  .0531{col 43}-3.9752{col 52}0.000{col 60} -.31513{col 73}-.106999
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      347{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.199{col 34}    0.199
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      328{col 34}      409

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19186{col 33} .04366{col 43}-4.3942{col 52}0.000{col 60}-.277433{col 73}-.106282
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.21107{col 33} .04366{col 43}-4.8342{col 52}0.000{col 60}-.296644{col 73}-.125494
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.21107{col 33} .05365{col 43}-3.9341{col 52}0.000{col 60}-.316223{col 73}-.105915
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      278{col 34}      340{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.192{col 34}    0.192
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      406

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19358{col 33} .04437{col 43}-4.3628{col 52}0.000{col 60}-.280542{col 73}-.106613
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.21065{col 33} .04437{col 43}-4.7476{col 52}0.000{col 60}-.297616{col 73}-.123687
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.21065{col 33}  .0543{col 43}-3.8797{col 52}0.000{col 60}-.317069{col 73}-.104233
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      270{col 34}      326{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.123{col 34}    0.123
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.184{col 34}    0.184
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      326{col 34}      405

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19476{col 33} .04529{col 43}-4.3001{col 52}0.000{col 60}-.283535{col 73}-.105992
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20935{col 33} .04529{col 43}-4.6222{col 52}0.000{col 60}-.298121{col 73}-.120578
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20935{col 33} .05518{col 43}-3.7940{col 52}0.000{col 60}-.317497{col 73}-.101201
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      317{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.118{col 34}    0.118
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.177{col 34}    0.177
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      320{col 34}      401

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19602{col 33} .04626{col 43}-4.2373{col 52}0.000{col 60}-.286692{col 73}-.105352
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20796{col 33} .04626{col 43}-4.4953{col 52}0.000{col 60}-.298625{col 73}-.117285
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20796{col 33} .05613{col 43}-3.7051{col 52}0.000{col 60}-.317963{col 73}-.097947
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      312{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.169{col 34}    0.169
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      317{col 34}      399

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19745{col 33}  .0474{col 43}-4.1653{col 52}0.000{col 60}-.290353{col 73} -.10454
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20737{col 33}  .0474{col 43}-4.3746{col 52}0.000{col 60}-.300274{col 73}-.114461
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20737{col 33} .05717{col 43}-3.6270{col 52}0.000{col 60}-.319426{col 73}-.095309
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      241{col 34}      302{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.162{col 34}    0.162
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      310{col 34}      389

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19914{col 33} .04863{col 43}-4.0953{col 52}0.000{col 60}-.294451{col 73}-.103836
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20753{col 33} .04863{col 43}-4.2677{col 52}0.000{col 60}-.302834{col 73}-.112219
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20753{col 33} .05832{col 43}-3.5581{col 52}0.000{col 60} -.32184{col 73}-.093213
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      234{col 34}      294{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.154{col 34}    0.154
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      304{col 34}      379

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19938{col 33} .04969{col 43}-4.0127{col 52}0.000{col 60}-.296766{col 73}-.101994
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20831{col 33} .04969{col 43}-4.1925{col 52}0.000{col 60}-.305699{col 73}-.110928
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20831{col 33} .05951{col 43}-3.5005{col 52}0.000{col 60} -.32495{col 73}-.091678
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      224{col 34}      288{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.098{col 34}    0.098
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      296{col 34}      366

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20019{col 33} .05074{col 43}-3.9457{col 52}0.000{col 60}-.299636{col 73}-.100749
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20958{col 33} .05074{col 43}-4.1307{col 52}0.000{col 60}-.309023{col 73}-.110136
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20958{col 33} .06077{col 43}-3.4487{col 52}0.001{col 60}-.328688{col 73} -.09047
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      217{col 34}      274{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.139{col 34}    0.139
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      285{col 34}      353

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20119{col 33}  .0518{col 43}-3.8838{col 52}0.000{col 60}-.302716{col 73}-.099656
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20911{col 33}  .0518{col 43}-4.0367{col 52}0.000{col 60}-.310637{col 73}-.107577
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20911{col 33} .06199{col 43}-3.3730{col 52}0.001{col 60}-.330615{col 73}-.087599
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      268{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.132{col 34}    0.132
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      346

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20115{col 33} .05303{col 43}-3.7929{col 52}0.000{col 60}-.305088{col 73}-.097205
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.2071{col 33} .05303{col 43}-3.9052{col 52}0.000{col 60}-.311045{col 73}-.103162
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.2071{col 33} .06304{col 43}-3.2852{col 52}0.001{col 60}-.330662{col 73}-.083545
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      203{col 34}      256{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      274{col 34}      332

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20193{col 33} .05443{col 43}-3.7101{col 52}0.000{col 60}-.308602{col 73}-.095253
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20607{col 33} .05443{col 43}-3.7862{col 52}0.000{col 60}-.312747{col 73}-.099397
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20607{col 33} .06451{col 43}-3.1944{col 52}0.001{col 60}-.332508{col 73}-.079636
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      198{col 34}      247{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      315

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20174{col 33} .05593{col 43}-3.6072{col 52}0.000{col 60} -.31136{col 73}-.092127
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20441{col 33} .05593{col 43}-3.6548{col 52}0.000{col 60}-.314024{col 73} -.09479
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20441{col 33} .06622{col 43}-3.0867{col 52}0.002{col 60}  -.3342{col 73}-.074614
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      236{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      304

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20145{col 33} .05771{col 43}-3.4909{col 52}0.000{col 60}-.314556{col 73}-.088346
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20186{col 33} .05771{col 43}-3.4980{col 52}0.000{col 60}-.314965{col 73}-.088755
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20186{col 33} .06847{col 43}-2.9481{col 52}0.003{col 60}-.336059{col 73}-.067661
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      176{col 34}      217{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      233{col 34}      294

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19934{col 33} .05939{col 43}-3.3565{col 52}0.001{col 60}-.315743{col 73}-.082941
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.19881{col 33} .05939{col 43}-3.3476{col 52}0.001{col 60}-.315212{col 73} -.08241
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.19881{col 33} .07052{col 43}-2.8191{col 52}0.005{col 60}-.337034{col 73}-.060588
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      167{col 34}      203{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      219{col 34}      275

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19547{col 33}  .0608{col 43}-3.2152{col 52}0.001{col 60}-.314628{col 73}-.076311
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.19204{col 33}  .0608{col 43}-3.1588{col 52}0.002{col 60}  -.3112{col 73}-.072884
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.19204{col 33} .07214{col 43}-2.6622{col 52}0.008{col 60}-.333425{col 73}-.050659
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      162{col 34}      190{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      212{col 34}      267

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19241{col 33} .06223{col 43}-3.0920{col 52}0.002{col 60}-.314371{col 73}-.070446
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1878{col 33} .06223{col 43}-3.0180{col 52}0.003{col 60}-.309766{col 73} -.06584
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1878{col 33} .07377{col 43}-2.5459{col 52}0.011{col 60}-.332386{col 73} -.04322
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      151{col 34}      176{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      199{col 34}      250

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19093{col 33} .06422{col 43}-2.9728{col 52}0.003{col 60}-.316805{col 73} -.06505
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18294{col 33} .06422{col 43}-2.8485{col 52}0.004{col 60}-.308822{col 73}-.057068
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18294{col 33} .07554{col 43}-2.4219{col 52}0.015{col 60}-.330994{col 73}-.034896
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      137{col 34}      165{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      184{col 34}      231

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1915{col 33} .06684{col 43}-2.8651{col 52}0.004{col 60}-.322506{col 73}-.060501
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17985{col 33} .06684{col 43}-2.6908{col 52}0.007{col 60}-.310851{col 73}-.048847
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17985{col 33} .07801{col 43}-2.3056{col 52}0.021{col 60}-.332738{col 73}-.026961
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      119{col 34}      142{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.043{col 34}    0.043
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      170{col 34}      206

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.19465{col 33} .06983{col 43}-2.7877{col 52}0.005{col 60}-.331511{col 73}-.057798
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18687{col 33} .06983{col 43}-2.6762{col 52}0.007{col 60}-.323727{col 73}-.050014
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18687{col 33} .08082{col 43}-2.3122{col 52}0.021{col 60}-.345272{col 73} -.02847
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      106{col 34}      128{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.038{col 34}    0.038
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.057{col 34}    0.057
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      161{col 34}      189

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20221{col 33} .07299{col 43}-2.7705{col 52}0.006{col 60}-.345271{col 73}-.059158
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.19952{col 33} .07299{col 43}-2.7335{col 52}0.006{col 60}-.342574{col 73} -.05646
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.19952{col 33} .08261{col 43}-2.4152{col 52}0.016{col 60}-.361431{col 73}-.037603
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       90{col 34}      111{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.033{col 34}    0.033
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.668{col 34}    0.668
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      144{col 34}      168

Outcome: fdonate_15any. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.20494{col 33} .07554{col 43}-2.7131{col 52}0.007{col 60}-.352989{col 73}-.056888
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.20299{col 33} .07554{col 43}-2.6872{col 52}0.007{col 60}-.351038{col 73}-.054937
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.20299{col 33} .08435{col 43}-2.4064{col 52}0.016{col 60}-.368314{col 73}-.037661
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 25
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 25.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E3_fdonate_15any.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      206{col 34}      263{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.134{col 34}    0.134
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      280{col 34}      349

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17469{col 33} .04849{col 43}-3.6023{col 52}0.000{col 60} -.26974{col 73}-.079645
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18436{col 33} .04849{col 43}-3.8017{col 52}0.000{col 60}-.279408{col 73}-.089313
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18436{col 33} .05687{col 43}-3.2416{col 52}0.001{col 60} -.29583{col 73} -.07289
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      316{col 34}      398{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.168{col 34}    0.168
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.269{col 34}    0.269
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      337{col 34}      432

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1511{col 33} .03574{col 43}-4.2277{col 52}0.000{col 60}-.221146{col 73}-.081047
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.16701{col 33} .03574{col 43}-4.6730{col 52}0.000{col 60}-.237061{col 73}-.096963
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.16701{col 33} .04418{col 43}-3.7801{col 52}0.000{col 60}-.253607{col 73}-.080416
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      311{col 34}      391{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.163{col 34}    0.163
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.261{col 34}    0.261
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      336{col 34}      430

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15202{col 33} .03614{col 43}-4.2065{col 52}0.000{col 60}-.222846{col 73}-.081186
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.16878{col 33} .03614{col 43}-4.6703{col 52}0.000{col 60}-.239607{col 73}-.097947
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.16878{col 33}  .0448{col 43}-3.7673{col 52}0.000{col 60}-.256585{col 73}-.080969
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      307{col 34}      383{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.158{col 34}    0.158
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.253{col 34}    0.253
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      333{col 34}      428

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15261{col 33} .03657{col 43}-4.1728{col 52}0.000{col 60}-.224288{col 73}-.080929
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17044{col 33} .03657{col 43}-4.6604{col 52}0.000{col 60}-.242121{col 73}-.098762
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17044{col 33} .04546{col 43}-3.7493{col 52}0.000{col 60} -.25954{col 73}-.081342
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      303{col 34}      379{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.153{col 34}    0.153
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.245{col 34}    0.245
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      333{col 34}      425

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15278{col 33} .03705{col 43}-4.1239{col 52}0.000{col 60}-.225396{col 73}-.080169
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17078{col 33} .03705{col 43}-4.6096{col 52}0.000{col 60}-.243392{col 73}-.098165
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17078{col 33} .04591{col 43}-3.7198{col 52}0.000{col 60}-.260762{col 73}-.080795
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      297{col 34}      368{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.237{col 34}    0.237
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      331{col 34}      421

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15329{col 33} .03753{col 43}-4.0842{col 52}0.000{col 60}-.226855{col 73}-.079728
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17152{col 33} .03753{col 43}-4.5699{col 52}0.000{col 60}-.245088{col 73} -.09796
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17152{col 33} .04642{col 43}-3.6952{col 52}0.000{col 60}-.262503{col 73}-.080545
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      291{col 34}      360{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.229{col 34}    0.229
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      330{col 34}      418

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15418{col 33} .03803{col 43}-4.0539{col 52}0.000{col 60}-.228716{col 73}-.079635
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17203{col 33} .03803{col 43}-4.5234{col 52}0.000{col 60} -.24657{col 73} -.09749
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17203{col 33} .04673{col 43}-3.6816{col 52}0.000{col 60}-.263614{col 73}-.080446
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      283{col 34}      351{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.221{col 34}    0.221
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      415

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15566{col 33} .03851{col 43}-4.0418{col 52}0.000{col 60}-.231143{col 73}-.080176
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17302{col 33} .03851{col 43}-4.4924{col 52}0.000{col 60}  -.2485{col 73}-.097533
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17302{col 33} .04709{col 43}-3.6745{col 52}0.000{col 60}-.265302{col 73}-.080731
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      347{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.213{col 34}    0.213
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      414

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15713{col 33} .03899{col 43}-4.0299{col 52}0.000{col 60} -.23355{col 73}-.080709
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17377{col 33} .03899{col 43}-4.4567{col 52}0.000{col 60}-.250191{col 73} -.09735
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17377{col 33} .04744{col 43}-3.6631{col 52}0.000{col 60}-.266747{col 73}-.080793
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      278{col 34}      340{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.205{col 34}    0.205
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      329{col 34}      412

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.15906{col 33}  .0396{col 43}-4.0164{col 52}0.000{col 60}-.236683{col 73}-.081442
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17489{col 33}  .0396{col 43}-4.4161{col 52}0.000{col 60}-.252512{col 73}-.097271
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17489{col 33} .04793{col 43}-3.6487{col 52}0.000{col 60}-.268837{col 73}-.080946
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      270{col 34}      326{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.123{col 34}    0.123
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.197{col 34}    0.197
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      408

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16057{col 33} .04042{col 43}-3.9728{col 52}0.000{col 60}-.239785{col 73}-.081354
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17528{col 33} .04042{col 43}-4.3367{col 52}0.000{col 60}-.254491{col 73} -.09606
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17528{col 33} .04857{col 43}-3.6084{col 52}0.000{col 60}-.270478{col 73}-.080073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      317{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.118{col 34}    0.118
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.189{col 34}    0.189
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      327{col 34}      406

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16229{col 33} .04128{col 43}-3.9318{col 52}0.000{col 60}-.243196{col 73}-.081391
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17554{col 33} .04128{col 43}-4.2527{col 52}0.000{col 60}-.256444{col 73}-.094639
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17554{col 33}  .0493{col 43}-3.5608{col 52}0.000{col 60}-.272164{col 73}-.078919
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      258{col 34}      312{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.181{col 34}    0.181
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      322{col 34}      403

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16435{col 33}  .0423{col 43}-3.8850{col 52}0.000{col 60} -.24726{col 73}-.081434
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17599{col 33}  .0423{col 43}-4.1601{col 52}0.000{col 60}  -.2589{col 73}-.093074
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17599{col 33} .05026{col 43}-3.5015{col 52}0.000{col 60}-.274495{col 73}-.077479
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      241{col 34}      302{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      318{col 34}      399

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16684{col 33} .04341{col 43}-3.8434{col 52}0.000{col 60}-.251923{col 73}-.081761
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17684{col 33} .04341{col 43}-4.0738{col 52}0.000{col 60}-.261923{col 73}-.091761
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17684{col 33} .05123{col 43}-3.4522{col 52}0.001{col 60}-.277242{col 73}-.076442
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      234{col 34}      294{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.165{col 34}    0.165
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      312{col 34}      391

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  -.168{col 33} .04437{col 43}-3.7863{col 52}0.000{col 60} -.25497{col 73}-.081037
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17723{col 33} .04437{col 43}-3.9943{col 52}0.000{col 60}-.264201{col 73}-.090269
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17723{col 33} .05228{col 43}-3.3904{col 52}0.001{col 60}-.279694{col 73}-.074776
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      224{col 34}      288{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.098{col 34}    0.098
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.157{col 34}    0.157
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      306{col 34}      383

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16976{col 33} .04532{col 43}-3.7454{col 52}0.000{col 60}-.258595{col 73}-.080926
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1792{col 33} .04532{col 43}-3.9537{col 52}0.000{col 60}-.268033{col 73}-.090364
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1792{col 33} .05337{col 43}-3.3575{col 52}0.001{col 60}-.283806{col 73}-.074592
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      217{col 34}      274{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.149{col 34}    0.149
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      297{col 34}      373

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17181{col 33}  .0463{col 43}-3.7108{col 52}0.000{col 60}-.262559{col 73}-.081066
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18252{col 33}  .0463{col 43}-3.9422{col 52}0.000{col 60} -.27327{col 73}-.091776
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18252{col 33} .05464{col 43}-3.3406{col 52}0.001{col 60}-.289611{col 73}-.075435
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      216{col 34}      268{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.141{col 34}    0.141
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      288{col 34}      356

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17298{col 33} .04743{col 43}-3.6469{col 52}0.000{col 60}-.265939{col 73}-.080013
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18377{col 33} .04743{col 43}-3.8744{col 52}0.000{col 60}-.276729{col 73}-.090803
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18377{col 33} .05593{col 43}-3.2855{col 52}0.001{col 60}-.293393{col 73} -.07414
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      203{col 34}      256{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      347

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17504{col 33}  .0487{col 43}-3.5941{col 52}0.000{col 60} -.27049{col 73}-.079584
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18444{col 33}  .0487{col 43}-3.7872{col 52}0.000{col 60}-.279894{col 73}-.088988
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18444{col 33} .05705{col 43}-3.2327{col 52}0.001{col 60}-.296266{col 73}-.072616
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      198{col 34}      247{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.125{col 34}    0.125
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      276{col 34}      332

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17547{col 33} .05008{col 43}-3.5041{col 52}0.000{col 60}-.273617{col 73}-.077324
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1837{col 33} .05008{col 43}-3.6684{col 52}0.000{col 60}-.281846{col 73}-.085553
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1837{col 33} .05848{col 43}-3.1410{col 52}0.002{col 60}-.298327{col 73}-.069072
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      189{col 34}      236{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      315

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17559{col 33} .05174{col 43}-3.3937{col 52}0.001{col 60}-.276995{col 73}-.074182
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.18272{col 33} .05174{col 43}-3.5315{col 52}0.000{col 60}-.284125{col 73}-.081312
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.18272{col 33} .06028{col 43}-3.0313{col 52}0.002{col 60}-.300859{col 73}-.064578
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      176{col 34}      217{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      245{col 34}      304

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17319{col 33} .05335{col 43}-3.2462{col 52}0.001{col 60}-.277751{col 73} -.06862
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1782{col 33} .05335{col 43}-3.3401{col 52}0.001{col 60}-.282764{col 73}-.073632
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1782{col 33} .06247{col 43}-2.8525{col 52}0.004{col 60}-.300636{col 73}-.055759
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      167{col 34}      203{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.101{col 34}    0.101
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      229{col 34}      292

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16872{col 33} .05473{col 43}-3.0829{col 52}0.002{col 60}-.275984{col 73}-.061457
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17234{col 33} .05473{col 43}-3.1490{col 52}0.002{col 60}-.279599{col 73}-.065072
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17234{col 33}  .0644{col 43}-2.6760{col 52}0.007{col 60} -.29856{col 73}-.046111
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      162{col 34}      190{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      217{col 34}      274

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16416{col 33} .05613{col 43}-2.9247{col 52}0.003{col 60}-.274171{col 73}-.054152
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.16399{col 33} .05613{col 43}-2.9217{col 52}0.003{col 60}-.274002{col 73}-.053983
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.16399{col 33} .06602{col 43}-2.4842{col 52}0.013{col 60} -.29338{col 73}-.034605
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      151{col 34}      176{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.085{col 34}    0.085
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      207{col 34}      263

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16168{col 33} .05801{col 43}-2.7871{col 52}0.005{col 60}-.275371{col 73} -.04798
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15763{col 33} .05801{col 43}-2.7173{col 52}0.007{col 60}-.271321{col 73} -.04393
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15763{col 33}  .0678{col 43}-2.3247{col 52}0.020{col 60}-.290518{col 73}-.024733
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      137{col 34}      165{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      198{col 34}      245

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.1617{col 33} .06039{col 43}-2.6776{col 52}0.007{col 60}-.280063{col 73}-.043336
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.15303{col 33} .06039{col 43}-2.5340{col 52}0.011{col 60}-.271392{col 73}-.034665
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.15303{col 33} .06952{col 43}-2.2012{col 52}0.028{col 60}-.289287{col 73} -.01677
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      119{col 34}      142{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.043{col 34}    0.043
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      178{col 34}      218

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.16594{col 33}   .063{col 43}-2.6339{col 52}0.008{col 60}-.289418{col 73}-.042461
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.1549{col 33}   .063{col 43}-2.4587{col 52}0.014{col 60}-.278377{col 73}-.031421
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.1549{col 33} .07165{col 43}-2.1619{col 52}0.031{col 60}-.295327{col 73}-.014471
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       778
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      339{col 34}      439{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      106{col 34}      128{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.038{col 34}    0.038
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.061{col 34}    0.061
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      164{col 34}      196

Outcome: fb5. Running variable: margin_victory.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.17815{col 33} .06559{col 43}-2.7161{col 52}0.007{col 60}-.306699{col 73}-.049594
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.17396{col 33} .06559{col 43}-2.6523{col 52}0.008{col 60}-.302513{col 73}-.045408
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.17396{col 33}  .0731{col 43}-2.3797{col 52}0.017{col 60}-.317238{col 73}-.030682
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 28
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 28.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_E3_fb5.pdf{rm}
saved as
PDF
format
{p_end}

{com}. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\FigH1_H2.do"
{txt}
{com}. clear all
{res}{txt}
{com}. set more off
{txt}
{com}.         
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\"  
{txt}
{com}. 
. cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}. 
. use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}. 
. 
. *Figure H1a
. rdplot donate_any15 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1757
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   38.059{col 37}   38.059
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       32{col 37}       33
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.189{col 37}    1.153
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.380{col 37}    0.380
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}       18
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       32{col 37}       33
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   10.667{col 37}    1.833
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.001{col 37}    0.140
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.999{col 37}    0.860
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure H1b
. rdplot b5 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1757
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   38.059{col 37}   38.059
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: b5. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       33{col 37}       34
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.153{col 37}    1.119
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.396{col 37}    0.376
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       22{col 37}       11
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       33{col 37}       34
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.500{col 37}    3.091
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.229{col 37}    0.033
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.771{col 37}    0.967
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure H1c
. rdplot runs_concejo rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1757
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      762{col 37}      995
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   38.059{col 37}   38.059
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       31{col 37}       31
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.228{col 37}    1.228
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.406{col 37}    0.418
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       32{col 37}       31
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       31{col 37}       31
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    0.969{col 37}    1.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.524{col 37}    0.500
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.476{col 37}    0.500
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
. 
. 
. *Figure H2a
. rdplot fdonate_any15 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       981
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      556
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      556
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   31.034{col 37}   34.337
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       22{col 37}       21
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.411{col 37}    1.635
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.498{col 37}    0.611
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        9{col 37}       16
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       22{col 37}       21
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.444{col 37}    1.313
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.064{col 37}    0.307
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.936{col 37}    0.693
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure H2b
. rdplot nfdonate_any15 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1007
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      582
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      582
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   38.059{col 37}   38.059
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       21{col 37}       22
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.812{col 37}    1.730
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.583{col 37}    0.610
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       10{col 37}       11
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       21{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.100{col 37}    2.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.097{col 37}    0.111
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.903{col 37}    0.889
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure H2c
. rdplot fb5 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       981
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      556
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      556
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   31.034{col 37}   34.337
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: fb5. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       22{col 37}       21
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.411{col 37}    1.635
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.498{col 37}    0.611
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       10{col 37}       13
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       22{col 37}       21
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    2.200{col 37}    1.615
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.086{col 37}    0.192
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.914{col 37}    0.808
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. *Figure H2d
. rdplot nfb5 rv2 ,  binselect(qsmv) p(3)
{res}
RD Plot with quantile spaced mimicking variance quantile spaced using spacings estimators.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}      1007
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      582
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      425{col 37}      582
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}   38.059{col 37}   38.059
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: nfb5. Running variable: rv2.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}       22{col 37}       22
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    1.730{col 37}    1.730
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.580{col 37}    0.610
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}       13{col 37}       14
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       22{col 37}       22
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}    1.692{col 37}    1.571
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.171{col 37}    0.205
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    0.829{col 37}    0.795
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. 
. 
. 
. 
{txt}end of do-file

{com}. do "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Code\FigH4_H5.do"
{txt}
{com}.         ***********************************************************************
.         *Name:                  Tables_Figures.do
.         *Project:               Network persistance
.         *Description:   Runs models of effect of winning
.         ***********************************************************************
.         *Main globals 
. global dir = "C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS"   
{txt}
{com}. 
. 
. 
. 
. 
.         ********************************************
.         *       BANDWIDTH FIGURES
.         ********************************************
. 
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}.         replace rv2=rv2/100
{txt}(1,743 real changes made)

{com}.         
.         cd "$dir\Figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         **Here is where the running variable goes.
.         foreach x in rv2 {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in donate_any15 b5 runs_concejo {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_H4_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      469{col 34}      614{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.057{col 34}    0.057
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.106{col 34}    0.106
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04675{col 33} .03902{col 43}-1.1981{col 52}0.231{col 60}-.123225{col 73} .029725
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05675{col 33} .03902{col 43}-1.4545{col 52}0.146{col 60}-.133226{col 73} .019724
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05675{col 33} .04414{col 43}-1.2857{col 52}0.199{col 60}-.143267{col 73} .029764
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      644{col 34}      854{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.214{col 34}    0.214
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      444{col 34}      495

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02089{col 33} .02946{col 43}-0.7090{col 52}0.478{col 60}-.078627{col 73} .036854
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02181{col 33} .02946{col 43}-0.7403{col 52}0.459{col 60}-.079551{col 73}  .03593
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02181{col 33} .03372{col 43}-0.6469{col 52}0.518{col 60}-.087895{col 73} .044273
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      634{col 34}      841{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.205{col 34}    0.205
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      443{col 34}      495

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02289{col 33} .02988{col 43}-0.7660{col 52}0.444{col 60}-.081456{col 73} .035676
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02419{col 33} .02988{col 43}-0.8094{col 52}0.418{col 60}-.082752{col 73} .034381
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02419{col 33} .03418{col 43}-0.7075{col 52}0.479{col 60}-.091187{col 73} .042816
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      629{col 34}      831{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.104{col 34}    0.104
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.195{col 34}    0.195
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      443{col 34}      491

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02471{col 33} .03031{col 43}-0.8152{col 52}0.415{col 60}-.084118{col 73}   .0347
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02671{col 33} .03031{col 43}-0.8812{col 52}0.378{col 60}-.086119{col 73} .032698
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02671{col 33} .03465{col 43}-0.7708{col 52}0.441{col 60}-.094627{col 73} .041207
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      620{col 34}      818{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.186{col 34}    0.186
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      442{col 34}      491

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02668{col 33} .03082{col 43}-0.8656{col 52}0.387{col 60}-.087078{col 73} .033725
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02965{col 33} .03082{col 43}-0.9621{col 52}0.336{col 60} -.09005{col 73} .030753
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02965{col 33} .03525{col 43}-0.8410{col 52}0.400{col 60}-.098744{col 73} .039446
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      604{col 34}      798{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.176{col 34}    0.176
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      437{col 34}      487

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0285{col 33} .03139{col 43}-0.9080{col 52}0.364{col 60}-.090016{col 73} .033017
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03281{col 33} .03139{col 43}-1.0453{col 52}0.296{col 60}-.094325{col 73} .028708
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03281{col 33} .03602{col 43}-0.9109{col 52}0.362{col 60}-.103405{col 73} .037788
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      592{col 34}      786{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.167{col 34}    0.167
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      432{col 34}      487

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03049{col 33}   .032{col 43}-0.9526{col 52}0.341{col 60}-.093215{col 73} .032239
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0356{col 33}   .032{col 43}-1.1123{col 52}0.266{col 60}-.098325{col 73} .027129
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0356{col 33} .03676{col 43}-0.9684{col 52}0.333{col 60}-.107646{col 73} .036449
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      572{col 34}      765{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.158{col 34}    0.158
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      429{col 34}      485

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03266{col 33} .03271{col 43}-0.9983{col 52}0.318{col 60}-.096778{col 73}  .03146
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03852{col 33} .03271{col 43}-1.1775{col 52}0.239{col 60}-.102641{col 73} .025597
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03852{col 33} .03762{col 43}-1.0240{col 52}0.306{col 60}-.112251{col 73} .035207
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      562{col 34}      746{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      427{col 34}      482

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03522{col 33} .03343{col 43}-1.0534{col 52}0.292{col 60}-.100746{col 73} .030311
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04179{col 33} .03343{col 43}-1.2501{col 52}0.211{col 60}-.107323{col 73} .023734
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04179{col 33} .03848{col 43}-1.0860{col 52}0.277{col 60}-.117221{col 73} .033632
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      545{col 34}      724{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.139{col 34}    0.139
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      423{col 34}      476

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03763{col 33}  .0344{col 43}-1.0939{col 52}0.274{col 60}-.105044{col 73}  .02979
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04597{col 33}  .0344{col 43}-1.3365{col 52}0.181{col 60}-.113388{col 73} .021446
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04597{col 33}  .0395{col 43}-1.1638{col 52}0.244{col 60}-.123389{col 73} .031446
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      525{col 34}      690{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      417{col 34}      472

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04026{col 33} .03557{col 43}-1.1319{col 52}0.258{col 60}-.109964{col 73} .029453
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05029{col 33} .03557{col 43}-1.4140{col 52}0.157{col 60}-.119998{col 73} .019419
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05029{col 33} .04067{col 43}-1.2366{col 52}0.216{col 60}-.129995{col 73} .029416
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      501{col 34}      659{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.120{col 34}    0.120
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      413{col 34}      469

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0422{col 33} .03686{col 43}-1.1449{col 52}0.252{col 60}-.114452{col 73} .030043
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05356{col 33} .03686{col 43}-1.4531{col 52}0.146{col 60}-.125811{col 73} .018684
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05356{col 33} .04196{col 43}-1.2764{col 52}0.202{col 60}-.135811{col 73} .028685
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      479{col 34}      630{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      403{col 34}      460

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04503{col 33} .03831{col 43}-1.1755{col 52}0.240{col 60}-.120105{col 73} .030051
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05568{col 33} .03831{col 43}-1.4535{col 52}0.146{col 60}-.130754{col 73} .019402
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05568{col 33} .04347{col 43}-1.2809{col 52}0.200{col 60}-.140868{col 73} .029515
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      453{col 34}      596{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.101{col 34}    0.101
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      398{col 34}      453

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04885{col 33} .03985{col 43}-1.2257{col 52}0.220{col 60}-.126961{col 73} .029263
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05819{col 33} .03985{col 43}-1.4600{col 52}0.144{col 60}  -.1363{col 73} .019924
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05819{col 33} .04497{col 43}-1.2940{col 52}0.196{col 60} -.14632{col 73} .029945
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      434{col 34}      560{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      447

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05277{col 33} .04132{col 43}-1.2772{col 52}0.202{col 60}-.133761{col 73} .028211
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06146{col 33} .04132{col 43}-1.4873{col 52}0.137{col 60}-.142442{col 73} .019531
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06146{col 33} .04657{col 43}-1.3197{col 52}0.187{col 60}-.152727{col 73} .029816
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      416{col 34}      525{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      372{col 34}      432

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05438{col 33} .04287{col 43}-1.2685{col 52}0.205{col 60}-.138394{col 73}  .02964
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06233{col 33} .04287{col 43}-1.4540{col 52}0.146{col 60}-.146345{col 73}  .02169
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06233{col 33} .04836{col 43}-1.2889{col 52}0.197{col 60}-.157106{col 73} .032451
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      386{col 34}      485{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      359{col 34}      419

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05304{col 33} .04489{col 43}-1.1816{col 52}0.237{col 60}-.141014{col 73}  .03494
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05993{col 33} .04489{col 43}-1.3351{col 52}0.182{col 60}-.147905{col 73}  .02805
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05993{col 33} .05056{col 43}-1.1853{col 52}0.236{col 60}-.159021{col 73} .039166
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      360{col 34}      439{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      338{col 34}      388

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04976{col 33} .04728{col 43}-1.0525{col 52}0.293{col 60}-.142433{col 73} .042904
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05668{col 33} .04728{col 43}-1.1988{col 52}0.231{col 60}-.149348{col 73} .035989
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05668{col 33} .05358{col 43}-1.0578{col 52}0.290{col 60}-.161699{col 73}  .04834
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      317{col 34}      390{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.029{col 34}    0.029
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      320{col 34}      368

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05074{col 33} .05083{col 43}-0.9983{col 52}0.318{col 60}-.150362{col 73} .048878
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05528{col 33} .05083{col 43}-1.0876{col 52}0.277{col 60}-.154899{col 73} .044341
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05528{col 33}  .0579{col 43}-0.9547{col 52}0.340{col 60}-.168761{col 73} .058203
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      334{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.024{col 34}    0.024
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.045{col 34}    0.045
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.533{col 34}    0.533
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      305{col 34}      338

Outcome: donate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05632{col 33} .05507{col 43}-1.0228{col 52}0.306{col 60}-.164255{col 73} .051608
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0552{col 33} .05507{col 43}-1.0024{col 52}0.316{col 60} -.16313{col 73} .052733
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0552{col 33} .06275{col 43}-0.8796{col 52}0.379{col 60}-.178188{col 73} .067791
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 20
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 20.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H4_donate_any15.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      543{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      382{col 34}      442

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06746{col 33} .03738{col 43}-1.8046{col 52}0.071{col 60}-.140734{col 73} .005807
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07881{col 33} .03738{col 43}-2.1080{col 52}0.035{col 60}-.152077{col 73}-.005535
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07881{col 33} .04213{col 43}-1.8704{col 52}0.061{col 60}-.161386{col 73} .003774
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      604{col 34}      798{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      434{col 34}      487

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03676{col 33} .02839{col 43}-1.2950{col 52}0.195{col 60}-.092394{col 73} .018874
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04594{col 33} .02839{col 43}-1.6183{col 52}0.106{col 60}-.101569{col 73} .009699
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04594{col 33} .03256{col 43}-1.4109{col 52}0.158{col 60}-.109748{col 73} .017878
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      592{col 34}      786{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.164{col 34}    0.164
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      430{col 34}      486

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0393{col 33} .02895{col 43}-1.3578{col 52}0.175{col 60}-.096041{col 73} .017432
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04939{col 33} .02895{col 43}-1.7061{col 52}0.088{col 60}-.106123{col 73}  .00735
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04939{col 33} .03317{col 43}-1.4887{col 52}0.137{col 60}-.114407{col 73} .015634
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      572{col 34}      765{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.154{col 34}    0.154
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      429{col 34}      483

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04213{col 33} .02959{col 43}-1.4237{col 52}0.155{col 60}-.100125{col 73} .015867
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0531{col 33} .02959{col 43}-1.7945{col 52}0.073{col 60}-.111097{col 73} .004895
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0531{col 33} .03391{col 43}-1.5661{col 52}0.117{col 60}-.119556{col 73} .013354
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      562{col 34}      746{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.145{col 34}    0.145
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      426{col 34}      481

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04508{col 33} .03024{col 43}-1.4905{col 52}0.136{col 60} -.10435{col 73} .014197
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05745{col 33} .03024{col 43}-1.8998{col 52}0.057{col 60}-.116728{col 73}  .00182
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05745{col 33} .03464{col 43}-1.6584{col 52}0.097{col 60}-.125354{col 73} .010446
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      545{col 34}      724{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.136{col 34}    0.136
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      475

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04789{col 33} .03108{col 43}-1.5407{col 52}0.123{col 60}-.108804{col 73}  .01303
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06199{col 33} .03108{col 43}-1.9945{col 52}0.046{col 60}-.122907{col 73}-.001073
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06199{col 33} .03553{col 43}-1.7449{col 52}0.081{col 60}-.131621{col 73} .007641
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      525{col 34}      690{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.127{col 34}    0.127
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      416{col 34}      470

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05119{col 33} .03207{col 43}-1.5965{col 52}0.110{col 60}-.114043{col 73} .011654
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06613{col 33} .03207{col 43}-2.0623{col 52}0.039{col 60}-.128978{col 73}-.003281
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06613{col 33} .03647{col 43}-1.8132{col 52}0.070{col 60}-.137614{col 73} .005354
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      501{col 34}      659{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.118{col 34}    0.118
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      412{col 34}      468

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05498{col 33} .03316{col 43}-1.6581{col 52}0.097{col 60}-.119975{col 73}  .01001
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06954{col 33} .03316{col 43}-2.0971{col 52}0.036{col 60}-.134533{col 73}-.004547
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06954{col 33} .03758{col 43}-1.8505{col 52}0.064{col 60}-.143195{col 73} .004115
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      479{col 34}      630{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.109{col 34}    0.109
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05917{col 33} .03439{col 43}-1.7205{col 52}0.085{col 60}-.126566{col 73} .008236
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07219{col 33} .03439{col 43}-2.0993{col 52}0.036{col 60}-.139595{col 73}-.004793
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07219{col 33} .03883{col 43}-1.8594{col 52}0.063{col 60}-.148292{col 73} .003905
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      453{col 34}      596{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      395{col 34}      451

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0632{col 33} .03574{col 43}-1.7683{col 52}0.077{col 60}-.133251{col 73} .006852
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07508{col 33} .03574{col 43}-2.1007{col 52}0.036{col 60}-.145134{col 73}-.005031
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07508{col 33} .04017{col 43}-1.8690{col 52}0.062{col 60}-.153819{col 73} .003654
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      434{col 34}      560{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.090{col 34}    0.090
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      388{col 34}      446

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06671{col 33}   .037{col 43}-1.8030{col 52}0.071{col 60}-.139223{col 73} .005806
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07815{col 33}   .037{col 43}-2.1123{col 52}0.035{col 60}-.150665{col 73}-.005636
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07815{col 33} .04163{col 43}-1.8774{col 52}0.060{col 60}-.159737{col 73} .003436
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      416{col 34}      525{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.081{col 34}    0.081
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      368{col 34}      430

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06919{col 33} .03834{col 43}-1.8046{col 52}0.071{col 60} -.14433{col 73} .005957
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0795{col 33} .03834{col 43}-2.0735{col 52}0.038{col 60}-.154639{col 73}-.004352
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0795{col 33} .04321{col 43}-1.8396{col 52}0.066{col 60}-.164194{col 73} .005203
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      386{col 34}      485{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      356{col 34}      413

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06929{col 33} .04007{col 43}-1.7295{col 52}0.084{col 60}-.147822{col 73} .009233
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07913{col 33} .04007{col 43}-1.9749{col 52}0.048{col 60}-.157654{col 73}-.000599
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07913{col 33} .04514{col 43}-1.7531{col 52}0.080{col 60}-.167593{col 73} .009339
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      360{col 34}      439{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      335{col 34}      386

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0668{col 33} .04203{col 43}-1.5891{col 52}0.112{col 60}-.149184{col 73} .015588
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07476{col 33} .04203{col 43}-1.7786{col 52}0.075{col 60}-.157151{col 73} .007622
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07476{col 33} .04764{col 43}-1.5694{col 52}0.117{col 60}-.168134{col 73} .018605
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      317{col 34}      390{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.029{col 34}    0.029
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      318{col 34}      362

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06787{col 33} .04501{col 43}-1.5080{col 52}0.132{col 60}-.156079{col 73} .020339
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07157{col 33} .04501{col 43}-1.5903{col 52}0.112{col 60}-.159781{col 73} .016637
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07157{col 33} .05133{col 43}-1.3943{col 52}0.163{col 60}-.172184{col 73}  .02904
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      334{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.024{col 34}    0.024
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      304{col 34}      332

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07337{col 33} .04886{col 43}-1.5015{col 52}0.133{col 60}-.169141{col 73} .022403
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07316{col 33} .04886{col 43}-1.4972{col 52}0.134{col 60}-.168934{col 73} .022611
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07316{col 33} .05586{col 43}-1.3098{col 52}0.190{col 60}-.182638{col 73} .036315
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      217{col 34}      262{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.019{col 34}    0.019
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.035{col 34}    0.035
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.544{col 34}    0.544
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      275{col 34}      300

Outcome: b5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07792{col 33} .05567{col 43}-1.3996{col 52}0.162{col 60} -.18703{col 73} .031197
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08037{col 33} .05567{col 43}-1.4436{col 52}0.149{col 60}-.189482{col 73} .028745
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08037{col 33} .06379{col 43}-1.2599{col 52}0.208{col 60}-.205395{col 73} .044658
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 17
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 17.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H4_b5.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      426{col 34}      543{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      390{col 34}      448

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03203{col 33} .06285{col 43}0.5097{col 52}0.610{col 60}-.091151{col 73}  .15522
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01198{col 33} .06285{col 43}0.1906{col 52}0.849{col 60}-.111206{col 73} .135165
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01198{col 33} .07053{col 43}0.1699{col 52}0.865{col 60}-.126254{col 73} .150213
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      604{col 34}      798{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.094{col 34}    0.094
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.187{col 34}    0.187
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      442{col 34}      491

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08688{col 33} .04749{col 43}1.8293{col 52}0.067{col 60}-.006205{col 73} .179961
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .05843{col 33} .04749{col 43}1.2303{col 52}0.219{col 60}-.034653{col 73} .151513
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .05843{col 33} .05352{col 43}1.0916{col 52}0.275{col 60}-.046476{col 73} .163336
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      592{col 34}      786{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.177{col 34}    0.177
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      437{col 34}      487

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08219{col 33} .04837{col 43}1.6992{col 52}0.089{col 60}-.012611{col 73} .176999
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .05292{col 33} .04837{col 43}1.0940{col 52}0.274{col 60}-.041885{col 73} .147725
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .05292{col 33} .05464{col 43}0.9685{col 52}0.333{col 60}-.054179{col 73} .160019
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      572{col 34}      765{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.167{col 34}    0.167
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      432{col 34}      487

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .07614{col 33} .04941{col 43}1.5411{col 52}0.123{col 60}-.020694{col 73} .172972
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04875{col 33} .04941{col 43}0.9867{col 52}0.324{col 60}-.048085{col 73} .145581
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04875{col 33} .05575{col 43}0.8744{col 52}0.382{col 60}-.060517{col 73} .158013
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      562{col 34}      746{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.157{col 34}    0.157
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      429{col 34}      484

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .07251{col 33}  .0505{col 43}1.4359{col 52}0.151{col 60}-.026467{col 73} .171497
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04661{col 33}  .0505{col 43}0.9230{col 52}0.356{col 60}-.052371{col 73} .145593
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04661{col 33} .05698{col 43}0.8180{col 52}0.413{col 60}-.065065{col 73} .158287
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      545{col 34}      724{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.074{col 34}    0.074
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      427{col 34}      482

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06831{col 33} .05195{col 43}1.3149{col 52}0.189{col 60}-.033509{col 73}  .17012
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04439{col 33} .05195{col 43}0.8545{col 52}0.393{col 60}-.057424{col 73} .146204
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04439{col 33}  .0586{col 43}0.7575{col 52}0.449{col 60} -.07047{col 73}  .15925
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      525{col 34}      690{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.137{col 34}    0.137
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      421{col 34}      476

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06109{col 33} .05373{col 43}1.1371{col 52}0.255{col 60}-.044207{col 73} .166396
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03868{col 33} .05373{col 43}0.7199{col 52}0.472{col 60}-.066623{col 73}  .14398
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03868{col 33} .06068{col 43}0.6374{col 52}0.524{col 60} -.08026{col 73} .157617
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      501{col 34}      659{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.064{col 34}    0.064
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.127{col 34}    0.127
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      417{col 34}      471

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05546{col 33} .05575{col 43}0.9948{col 52}0.320{col 60}-.053809{col 73} .164726
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03346{col 33} .05575{col 43}0.6002{col 52}0.548{col 60}-.075807{col 73} .142728
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03346{col 33} .06288{col 43}0.5321{col 52}0.595{col 60}-.089783{col 73} .156704
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      479{col 34}      630{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.059{col 34}    0.059
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      412{col 34}      468

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05129{col 33} .05791{col 43}0.8857{col 52}0.376{col 60}-.062214{col 73} .164802
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .03041{col 33} .05791{col 43}0.5251{col 52}0.599{col 60}-.083095{col 73} .143921
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .03041{col 33} .06513{col 43}0.4670{col 52}0.641{col 60}-.097235{col 73}  .15806
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      453{col 34}      596{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.054{col 34}    0.054
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.107{col 34}    0.107
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      400{col 34}      456

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .04491{col 33} .06006{col 43}0.7478{col 52}0.455{col 60}-.072796{col 73} .162621
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .02615{col 33} .06006{col 43}0.4353{col 52}0.663{col 60}-.091563{col 73} .143854
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .02615{col 33} .06741{col 43}0.3879{col 52}0.698{col 60}-.105971{col 73} .158262
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      434{col 34}      560{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.049{col 34}    0.049
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      394{col 34}      450

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03479{col 33} .06214{col 43}0.5599{col 52}0.576{col 60}-.087005{col 73} .156592
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .01542{col 33} .06214{col 43}0.2481{col 52}0.804{col 60} -.10638{col 73} .137217
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .01542{col 33} .06969{col 43}0.2212{col 52}0.825{col 60} -.12117{col 73} .152006
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      416{col 34}      525{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      382{col 34}      442

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .02331{col 33} .06456{col 43}0.3610{col 52}0.718{col 60} -.10323{col 73} .149848
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00407{col 33} .06456{col 43}0.0631{col 52}0.950{col 60}-.122465{col 73} .130614
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00407{col 33} .07246{col 43}0.0562{col 52}0.955{col 60}-.137942{col 73} .146091
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      386{col 34}      485{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.039{col 34}    0.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      366{col 34}      428

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00976{col 33}  .0677{col 43}0.1442{col 52}0.885{col 60}-.122935{col 73}  .14246
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00895{col 33}  .0677{col 43}-0.1322{col 52}0.895{col 60}-.141649{col 73} .123747
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00895{col 33} .07575{col 43}-0.1182{col 52}0.906{col 60}-.157425{col 73} .139522
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      360{col 34}      439{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.034{col 34}    0.034
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      347{col 34}      398

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00731{col 33} .07121{col 43}-0.1027{col 52}0.918{col 60}-.146887{col 73}  .13226
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02673{col 33} .07121{col 43}-0.3754{col 52}0.707{col 60}-.166306{col 73} .112842
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02673{col 33} .07993{col 43}-0.3344{col 52}0.738{col 60}-.183394{col 73} .129931
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      317{col 34}      390{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.029{col 34}    0.029
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      328{col 34}      373

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02182{col 33}  .0762{col 43}-0.2863{col 52}0.775{col 60}-.171176{col 73} .127535
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04804{col 33}  .0762{col 43}-0.6304{col 52}0.528{col 60}-.197393{col 73} .101317
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04804{col 33} .08543{col 43}-0.5623{col 52}0.574{col 60}-.215473{col 73} .119397
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      272{col 34}      334{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.024{col 34}    0.024
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      310{col 34}      344

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04103{col 33} .08264{col 43}-0.4964{col 52}0.620{col 60}-.203002{col 73}  .12095
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07075{col 33} .08264{col 43}-0.8560{col 52}0.392{col 60}-.232722{col 73}  .09123
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07075{col 33} .09306{col 43}-0.7603{col 52}0.447{col 60}-.253132{col 73} .111641
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1757
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      762{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      217{col 34}      262{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.019{col 34}    0.019
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.038{col 34}    0.038
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.503{col 34}    0.503
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      283{col 34}      310

Outcome: runs_concejo. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06249{col 33} .09301{col 43}-0.6719{col 52}0.502{col 60}-.244788{col 73} .119804
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08853{col 33} .09301{col 43}-0.9518{col 52}0.341{col 60}-.270824{col 73} .093768
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08853{col 33} .10422{col 43}-0.8495{col 52}0.396{col 60}-.292786{col 73} .115731
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 17
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 17.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H4_runs_concejo.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         
.         
.         use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}.                 
.                 replace rv2=rv2/100
{txt}(1,743 real changes made)

{com}.         cd "$figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}.         foreach y in fdonate_any15 fb5{c -(}
{txt}  2{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' rv2, all vce(cluster muni_code) p(1) level(95) 
{txt}  3{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  4{com}.                 local bw_double = `bw'*2
{txt}  5{com}.                 local bw_half = `bw'/2
{txt}  6{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  7{com}.                 local counter=1
{txt}  8{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt}  9{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 10{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 11{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 12{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 13{com}.                 while `j'>0 {c -(}
{txt} 14{com}.                         local counter = `counter'+1
{txt} 15{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 16{com}.                         rdrobust `y' rv2, all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 17{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 18{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 19{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 20{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 21{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 22{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 23{com}.                                 local j = 0
{txt} 24{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 25{com}.                                 local b = `bw_double'/`rho'
{txt} 26{com}.                                 rdrobust `y' rv2, all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 27{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 28{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 29{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 30{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 31{com}.                                         
.                         
.                         {c )-}
{txt} 32{com}.                         else {c -(}
{txt} 33{com}.                                 local j = 1
{txt} 34{com}.                         {c )-}   
{txt} 35{com}.         {c )-}
{txt} 36{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 37{com}.         forvalues i=1/`counter' {c -(}
{txt} 38{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 39{com}.                 mat graph[`i',2] = `b_`i''
{txt} 40{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 41{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 42{com}.                 
.         {c )-}
{txt} 43{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 44{com}.         preserve
{txt} 45{com}.         clear 
{txt} 46{com}.         svmat graph
{txt} 47{com}.         * graphs
.         local line_2 = round(`margin_victory_line2',0.001)
{txt} 48{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 49{com}.         
.         *Save graph
.         graph export "Fig_H5_`y'.pdf", as(pdf) replace
{txt} 50{com}.         
.         restore
{txt} 51{com}.         {c )-}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      277{col 34}      362{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.061{col 34}    0.061
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.099{col 34}    0.099
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      259{col 34}      299

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02599{col 33} .04635{col 43}-0.5608{col 52}0.575{col 60}-.116834{col 73}  .06485
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03188{col 33} .04635{col 43}-0.6879{col 52}0.492{col 60}-.122725{col 73} .058959
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03188{col 33} .05391{col 43}-0.5914{col 52}0.554{col 60}-.137545{col 73} .073778
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      376{col 34}      489{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.122{col 34}    0.122
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.197{col 34}    0.197
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      291{col 34}      338

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00706{col 33} .03531{col 43}-0.1999{col 52}0.842{col 60}-.076271{col 73} .062156
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01722{col 33} .03531{col 43}-0.4875{col 52}0.626{col 60} -.08643{col 73} .051996
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01722{col 33} .04222{col 43}-0.4078{col 52}0.683{col 60}-.099969{col 73} .065535
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      372{col 34}      486{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.117{col 34}    0.117
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.189{col 34}    0.189
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      291{col 34}      337

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00899{col 33} .03578{col 43}-0.2512{col 52}0.802{col 60}-.079113{col 73} .061135
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01967{col 33} .03578{col 43}-0.5498{col 52}0.582{col 60}-.089794{col 73} .050453
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01967{col 33} .04276{col 43}-0.4600{col 52}0.646{col 60}-.103488{col 73} .064147
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      367{col 34}      483{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.112{col 34}    0.112
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.181{col 34}    0.181
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      290{col 34}      335

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0113{col 33} .03632{col 43}-0.3112{col 52}0.756{col 60}-.082489{col 73} .059883
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02314{col 33} .03632{col 43}-0.6372{col 52}0.524{col 60}-.094331{col 73} .048041
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02314{col 33} .04355{col 43}-0.5314{col 52}0.595{col 60} -.10851{col 73}  .06222
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      360{col 34}      471{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.107{col 34}    0.107
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.173{col 34}    0.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      285{col 34}      333

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01375{col 33} .03687{col 43}-0.3730{col 52}0.709{col 60}-.086012{col 73} .058509
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02654{col 33} .03687{col 43}-0.7198{col 52}0.472{col 60}-.098797{col 73} .045723
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02654{col 33} .04439{col 43}-0.5978{col 52}0.550{col 60}-.113543{col 73} .060469
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      357{col 34}      469{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.165{col 34}    0.165
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      283{col 34}      333

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01581{col 33} .03753{col 43}-0.4212{col 52}0.674{col 60}-.089364{col 73} .057748
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02931{col 33} .03753{col 43}-0.7809{col 52}0.435{col 60}-.102862{col 73}  .04425
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02931{col 33} .04522{col 43}-0.6480{col 52}0.517{col 60} -.11794{col 73} .059328
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      351{col 34}      459{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.157{col 34}    0.157
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      281{col 34}      331

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01719{col 33} .03831{col 43}-0.4486{col 52}0.654{col 60}-.092276{col 73} .057905
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03153{col 33} .03831{col 43}-0.8230{col 52}0.411{col 60}-.106621{col 73}  .04356
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03153{col 33} .04626{col 43}-0.6816{col 52}0.495{col 60}-.122194{col 73} .059133
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      344{col 34}      450{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.149{col 34}    0.149
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      326

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01908{col 33} .03917{col 43}-0.4871{col 52}0.626{col 60}-.095844{col 73}  .05769
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03339{col 33} .03917{col 43}-0.8526{col 52}0.394{col 60} -.11016{col 73} .043374
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03339{col 33} .04721{col 43}-0.7074{col 52}0.479{col 60}-.125918{col 73} .059132
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      336{col 34}      440{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.141{col 34}    0.141
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      323

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02115{col 33} .04016{col 43}-0.5266{col 52}0.598{col 60}-.099852{col 73}  .05756
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03606{col 33} .04016{col 43}-0.8981{col 52}0.369{col 60}-.114769{col 73} .042643
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03606{col 33} .04821{col 43}-0.7481{col 52}0.454{col 60} -.13055{col 73} .058424
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      325{col 34}      425{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.082{col 34}    0.082
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      275{col 34}      322

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02358{col 33} .04114{col 43}-0.5731{col 52}0.567{col 60} -.10421{col 73} .057056
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03915{col 33} .04114{col 43}-0.9515{col 52}0.341{col 60}-.119779{col 73} .041488
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03915{col 33} .04912{col 43}-0.7969{col 52}0.425{col 60} -.13542{col 73} .057129
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      316{col 34}      413{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      273{col 34}      319

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02558{col 33} .04213{col 43}-0.6072{col 52}0.544{col 60}-.108151{col 73} .056993
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04065{col 33} .04213{col 43}-0.9649{col 52}0.335{col 60}-.123221{col 73} .041924
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04065{col 33} .04997{col 43}-0.8135{col 52}0.416{col 60}-.138581{col 73} .057283
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      308{col 34}      403{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      270{col 34}      317

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02728{col 33} .04335{col 43}-0.6293{col 52}0.529{col 60}-.112234{col 73} .057677
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04023{col 33} .04335{col 43}-0.9282{col 52}0.353{col 60}-.125186{col 73} .044724
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04023{col 33} .05108{col 43}-0.7876{col 52}0.431{col 60}-.140348{col 73} .059887
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      292{col 34}      381{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      262{col 34}      306

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02784{col 33} .04474{col 43}-0.6222{col 52}0.534{col 60}-.115522{col 73} .059847
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03695{col 33} .04474{col 43}-0.8259{col 52}0.409{col 60}-.124632{col 73} .050737
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03695{col 33}  .0524{col 43}-0.7051{col 52}0.481{col 60}-.139643{col 73} .065748
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      365{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.062{col 34}    0.062
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.100{col 34}    0.100
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      259{col 34}      302

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02606{col 33} .04614{col 43}-0.5648{col 52}0.572{col 60}-.116489{col 73} .064369
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03211{col 33} .04614{col 43}-0.6959{col 52}0.487{col 60}-.122536{col 73} .058323
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03211{col 33}  .0537{col 43}-0.5979{col 52}0.550{col 60}-.137347{col 73} .073135
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      267{col 34}      348{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.057{col 34}    0.057
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      254{col 34}      294

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02501{col 33} .04785{col 43}-0.5226{col 52}0.601{col 60}-.118793{col 73} .068781
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02898{col 33} .04785{col 43}-0.6055{col 52}0.545{col 60}-.122763{col 73} .064811
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02898{col 33} .05539{col 43}-0.5231{col 52}0.601{col 60}-.137547{col 73} .079596
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      255{col 34}      326{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.052{col 34}    0.052
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      243{col 34}      281

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02385{col 33} .04976{col 43}-0.4793{col 52}0.632{col 60}-.121386{col 73} .073682
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02462{col 33} .04976{col 43}-0.4948{col 52}0.621{col 60}-.122156{col 73} .072913
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02462{col 33} .05742{col 43}-0.4288{col 52}0.668{col 60}-.137165{col 73} .087922
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      243{col 34}      304{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.076{col 34}    0.076
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      237{col 34}      276

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02329{col 33} .05162{col 43}-0.4511{col 52}0.652{col 60}-.124469{col 73} .077894
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02016{col 33} .05162{col 43}-0.3905{col 52}0.696{col 60}-.121342{col 73} .081021
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02016{col 33}  .0594{col 43}-0.3394{col 52}0.734{col 60}-.136579{col 73} .096259
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      238{col 34}      289{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.042{col 34}    0.042
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      223{col 34}      259

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01995{col 33} .05365{col 43}-0.3719{col 52}0.710{col 60}-.125112{col 73} .085206
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01165{col 33} .05365{col 43}-0.2172{col 52}0.828{col 60} -.11681{col 73} .093508
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01165{col 33} .06203{col 43}-0.1878{col 52}0.851{col 60}-.133225{col 73} .109922
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      223{col 34}      266{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.037{col 34}    0.037
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.060{col 34}    0.060
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      216{col 34}      246

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01035{col 33} .05581{col 43}-0.1854{col 52}0.853{col 60}-.119731{col 73} .099036
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .00065{col 33} .05581{col 43}0.0116{col 52}0.991{col 60}-.108737{col 73}  .11003
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .00065{col 33} .06472{col 43}0.0100{col 52}0.992{col 60}-.126211{col 73} .127504
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      209{col 34}      245{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.032{col 34}    0.032
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.052{col 34}    0.052
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      206{col 34}      229

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .00355{col 33} .05848{col 43}0.0607{col 52}0.952{col 60}-.111071{col 73} .118165
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .02263{col 33} .05848{col 43}0.3869{col 52}0.699{col 60} -.09199{col 73} .137246
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .02263{col 33} .06863{col 43}0.3297{col 52}0.742{col 60}-.111887{col 73} .157143
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      179{col 34}      205{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.027{col 34}    0.027
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.044{col 34}    0.044
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.619{col 34}    0.619
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      197{col 34}      210

Outcome: fdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01768{col 33} .06216{col 43}0.2844{col 52}0.776{col 60}-.104155{col 73} .139518
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04609{col 33} .06216{col 43}0.7414{col 52}0.458{col 60} -.07575{col 73} .167923
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04609{col 33} .07328{col 43}0.6289{col 52}0.529{col 60}-.097532{col 73} .189705
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 21
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 21.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H5_fdonate_any15.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      264{col 34}      344{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.095{col 34}    0.095
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      255{col 34}      296

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03588{col 33} .04434{col 43}-0.8093{col 52}0.418{col 60}-.122792{col 73} .051023
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04619{col 33} .04434{col 43}-1.0418{col 52}0.298{col 60}-.133101{col 73} .040713
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04619{col 33} .05056{col 43}-0.9136{col 52}0.361{col 60}-.145297{col 73} .052909
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      367{col 34}      483{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.112{col 34}    0.112
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.191{col 34}    0.191
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      291{col 34}      337

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00807{col 33} .03342{col 43}-0.2415{col 52}0.809{col 60}-.073566{col 73} .057428
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02236{col 33} .03342{col 43}-0.6690{col 52}0.503{col 60}-.087854{col 73}  .04314
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02236{col 33} .03906{col 43}-0.5724{col 52}0.567{col 60}-.098909{col 73} .054195
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      360{col 34}      471{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.107{col 34}    0.107
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.182{col 34}    0.182
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      290{col 34}      335

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01149{col 33} .03391{col 43}-0.3389{col 52}0.735{col 60}-.077956{col 73}  .05497
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02722{col 33} .03391{col 43}-0.8027{col 52}0.422{col 60}-.093683{col 73} .039244
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02722{col 33} .03974{col 43}-0.6849{col 52}0.493{col 60}-.105109{col 73}  .05067
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      357{col 34}      469{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.174{col 34}    0.174
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      286{col 34}      334

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01479{col 33} .03451{col 43}-0.4285{col 52}0.668{col 60}-.082436{col 73}  .05286
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03189{col 33} .03451{col 43}-0.9238{col 52}0.356{col 60}-.099533{col 73} .035762
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03189{col 33}  .0406{col 43}-0.7853{col 52}0.432{col 60}-.111469{col 73} .047698
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      351{col 34}      459{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.165{col 34}    0.165
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      283{col 34}      333

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0173{col 33} .03522{col 43}-0.4911{col 52}0.623{col 60}-.086332{col 73} .051735
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03499{col 33} .03522{col 43}-0.9933{col 52}0.321{col 60} -.10402{col 73} .034047
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03499{col 33} .04143{col 43}-0.8446{col 52}0.398{col 60}-.116179{col 73} .046207
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      344{col 34}      450{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.092{col 34}    0.092
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.157{col 34}    0.157
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      281{col 34}      331

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01977{col 33} .03601{col 43}-0.5491{col 52}0.583{col 60}-.090352{col 73} .050806
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03834{col 33} .03601{col 43}-1.0646{col 52}0.287{col 60}-.108917{col 73} .032241
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03834{col 33} .04243{col 43}-0.9036{col 52}0.366{col 60}-.121493{col 73} .044817
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      336{col 34}      440{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      326

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02252{col 33} .03694{col 43}-0.6096{col 52}0.542{col 60}-.094919{col 73} .049882
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04165{col 33} .03694{col 43}-1.1275{col 52}0.260{col 60}-.114051{col 73}  .03075
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04165{col 33} .04345{col 43}-0.9587{col 52}0.338{col 60}-.126803{col 73} .043502
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      325{col 34}      425{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.082{col 34}    0.082
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.140{col 34}    0.140
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      279{col 34}      323

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02569{col 33} .03787{col 43}-0.6785{col 52}0.497{col 60} -.09991{col 73} .048526
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04659{col 33} .03787{col 43}-1.2303{col 52}0.219{col 60}-.120804{col 73} .027632
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04659{col 33} .04455{col 43}-1.0457{col 52}0.296{col 60}-.133903{col 73}  .04073
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      316{col 34}      413{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.077{col 34}    0.077
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.131{col 34}    0.131
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      274{col 34}      322

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02847{col 33} .03881{col 43}-0.7337{col 52}0.463{col 60}-.104533{col 73}  .04759
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05006{col 33} .03881{col 43}-1.2900{col 52}0.197{col 60}-.126124{col 73} .025999
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05006{col 33} .04551{col 43}-1.1001{col 52}0.271{col 60}-.139255{col 73}  .03913
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      308{col 34}      403{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.123{col 34}    0.123
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      272{col 34}      319

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03107{col 33} .03994{col 43}-0.7779{col 52}0.437{col 60}-.109338{col 73} .047207
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05167{col 33} .03994{col 43}-1.2939{col 52}0.196{col 60}-.129946{col 73} .026599
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05167{col 33} .04644{col 43}-1.1128{col 52}0.266{col 60}-.142685{col 73} .039338
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      292{col 34}      381{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.067{col 34}    0.067
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.114{col 34}    0.114
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      268{col 34}      317

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03338{col 33}  .0412{col 43}-0.8102{col 52}0.418{col 60}-.114126{col 73} .047369
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05119{col 33}  .0412{col 43}-1.2424{col 52}0.214{col 60}-.131933{col 73} .029561
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05119{col 33} .04759{col 43}-1.0756{col 52}0.282{col 60}-.144454{col 73} .042082
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      279{col 34}      365{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.062{col 34}    0.062
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.106{col 34}    0.106
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      262{col 34}      305

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0342{col 33} .04246{col 43}-0.8054{col 52}0.421{col 60}-.117416{col 73} .049021
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04799{col 33} .04246{col 43}-1.1303{col 52}0.258{col 60}-.131209{col 73} .035228
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04799{col 33} .04881{col 43}-0.9833{col 52}0.325{col 60} -.14365{col 73} .047668
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      267{col 34}      348{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.057{col 34}    0.057
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.097{col 34}    0.097
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      258{col 34}      298

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0356{col 33} .04398{col 43}-0.8094{col 52}0.418{col 60}-.121808{col 73} .050608
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04629{col 33} .04398{col 43}-1.0525{col 52}0.293{col 60}  -.1325{col 73} .039916
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04629{col 33} .05021{col 43}-0.9219{col 52}0.357{col 60}-.144706{col 73} .052122
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      255{col 34}      326{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.052{col 34}    0.052
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.089{col 34}    0.089
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      250{col 34}      288

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03741{col 33} .04558{col 43}-0.8209{col 52}0.412{col 60}-.126746{col 73} .051917
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04612{col 33} .04558{col 43}-1.0119{col 52}0.312{col 60}-.135453{col 73} .043209
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04612{col 33} .05177{col 43}-0.8909{col 52}0.373{col 60}-.147594{col 73}  .05535
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      243{col 34}      304{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.080{col 34}    0.080
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      238{col 34}      278

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}   -.04{col 33} .04709{col 43}-0.8492{col 52}0.396{col 60}-.132299{col 73} .052309
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04598{col 33} .04709{col 43}-0.9763{col 52}0.329{col 60}-.138284{col 73} .046324
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04598{col 33}  .0534{col 43}-0.8610{col 52}0.389{col 60}-.150644{col 73} .058684
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      238{col 34}      289{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.042{col 34}    0.042
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.072{col 34}    0.072
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      232{col 34}      270

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0405{col 33} .04868{col 43}-0.8320{col 52}0.405{col 60}-.135911{col 73} .054905
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04401{col 33} .04868{col 43}-0.9042{col 52}0.366{col 60}-.139422{col 73} .051395
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04401{col 33} .05519{col 43}-0.7975{col 52}0.425{col 60}-.152189{col 73} .064162
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      223{col 34}      266{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.037{col 34}    0.037
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      218{col 34}      251

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03578{col 33} .05026{col 43}-0.7118{col 52}0.477{col 60}-.134289{col 73} .062737
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03749{col 33} .05026{col 43}-0.7459{col 52}0.456{col 60}-.136002{col 73} .061024
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03749{col 33}  .0573{col 43}-0.6542{col 52}0.513{col 60}-.149803{col 73} .074824
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      209{col 34}      245{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.032{col 34}    0.032
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.055{col 34}    0.055
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      210{col 34}      240

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02827{col 33} .05215{col 43}-0.5421{col 52}0.588{col 60}-.130487{col 73} .073946
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02662{col 33} .05215{col 43}-0.5104{col 52}0.610{col 60}-.128837{col 73} .075596
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02662{col 33} .05985{col 43}-0.4448{col 52}0.656{col 60}-.143917{col 73} .090676
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       981
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      556{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      179{col 34}      205{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.027{col 34}    0.027
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.046{col 34}    0.046
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.587{col 34}    0.587
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      200{col 34}      218

Outcome: fb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02151{col 33}  .0548{col 43}-0.3925{col 52}0.695{col 60}-.128916{col 73} .085899
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01147{col 33}  .0548{col 43}-0.2093{col 52}0.834{col 60}-.118875{col 73}  .09594
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01147{col 33} .06331{col 43}-0.1811{col 52}0.856{col 60}-.135556{col 73} .112621
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 19
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 19.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H5_fb5.pdf{rm}
saved as
PDF
format
{p_end}

{com}.         
.         
.                 
.         
.         
.         cd "$dir"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS
{txt}
{com}.         use "$dir\Data\council_cand_level_persist_rep.dta",clear
{txt}
{com}.         replace rv2=rv2/100     
{txt}(1,743 real changes made)

{com}.         cd "$figures"
{res}C:\Users\mrueda\Documents\Emory\Papers\Networks_persistance\do_files\do_files_APSA21\post_JOP\Replication_BJPS\Figures
{txt}
{com}. 
.         
.         **Here is where the running variable goes.
.         foreach x in rv2 {c -(}
{txt}  2{com}.         **Here is where the outcome goes.
.         *foreach y in $outcomes {c -(}
.                 foreach y in nfdonate_any15 nfb5 {c -(}
{txt}  3{com}.                 ************
.                 * Linear
.                 *************
.                 *mserd approach, linear (get optimal bw)
.                 rdrobust `y' `x', all vce(cluster muni_code) p(1) level(95) 
{txt}  4{com}. 
.                 local bw=round(`e(h_r)',0.001)
{txt}  5{com}.                 local bw_double = `bw'*2
{txt}  6{com}.                 local bw_half = `bw'/2
{txt}  7{com}.                 local rho =  `e(h_r)'/`e(b_r)'
{txt}  8{com}.                 local counter=1
{txt}  9{com}.                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 10{com}.                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 11{com}.                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 12{com}.                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 13{com}. 
. 
.                 *According to Cattaneo, Idrobo and Titiunik, 
.                 *we should do double of the optimal bandwidht.
.                 local j = 1
{txt} 14{com}.                 while `j'>0 {c -(}
{txt} 15{com}.                         local counter = `counter'+1
{txt} 16{com}.                         
.                         *CTT approach
.                         local b = `bw_double'/`rho'
{txt} 17{com}.                         rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 18{com}.                         
.                         local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 19{com}.                         local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 20{com}.                         local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 21{com}.                         local bw_`counter' = round(`e(h_r)',0.001)
{txt} 22{com}.                         local bw_double = `bw_double'- (0.005)
{txt} 23{com}.                         
.                         if `bw_double'<=`bw_half' {c -(}
{txt} 24{com}.                                 local j = 0
{txt} 25{com}.                                 
.                                 * CTT approach
.                                 local counter = `counter'+1
{txt} 26{com}.                                 local b = `bw_double'/`rho'
{txt} 27{com}.                                 rdrobust `y' `x', all vce(cluster muni_code) level(95) h(`bw_double') b(`b')
{txt} 28{com}. 
.                                 local b_`counter' = round(`e(tau_cl)',0.001)
{txt} 29{com}.                                 local uci_`counter' = round(`e(ci_r_rb)',0.001)
{txt} 30{com}.                                 local lci_`counter' = round(`e(ci_l_rb)',0.001)
{txt} 31{com}.                                 local bw_`counter' = round(`e(h_r)',0.001)
{txt} 32{com}.                                         
.                         
.                         {c )-}
{txt} 33{com}.                         else {c -(}
{txt} 34{com}.                                 local j = 1
{txt} 35{com}.                         {c )-}   
{txt} 36{com}.         {c )-}
{txt} 37{com}. 
. 
.         matrix graph = J(`counter',4,.)
{txt} 38{com}.         forvalues i=1/`counter' {c -(}
{txt} 39{com}.                 mat graph[`i',1] = `bw_`i''
{txt} 40{com}.                 mat graph[`i',2] = `b_`i''
{txt} 41{com}.                 mat graph[`i',3] = `lci_`i''
{txt} 42{com}.                 mat graph[`i',4] = `uci_`i''
{txt} 43{com}.                 
.         {c )-}
{txt} 44{com}. 
.         mata : st_matrix("graph", sort(st_matrix("graph"), 1))
{txt} 45{com}.         preserve
{txt} 46{com}.         clear 
{txt} 47{com}.         svmat graph
{txt} 48{com}.         * graphs
.         local line_2 = round(`x_line2',0.001)
{txt} 49{com}.         *attacks
.         graph tw (sc graph2 graph1) (rcap graph4 graph3 graph1, lcolor(dkgreen)), title("") subtitle("") ///
>         xtitle("Margin Victory") ytitle("Point Estimate") xli(`bw') xlabel(#8) xscale(range(`bw_half' `bw_double')) legend(off)  graphregion(fcolor(white))  yline(0)
{txt} 50{com}.         
.         *Save graph
.         graph export "Fig_H5_`y'.pdf", as(pdf) replace
{txt} 51{com}.         
.         restore
{txt} 52{com}.         {c )-}
{txt} 53{com}.         {c )-}       
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      313{col 34}      432{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.079{col 34}    0.079
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      255{col 34}      304

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01958{col 33} .04802{col 43}-0.4077{col 52}0.683{col 60}-.113701{col 73}  .07454
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01886{col 33} .04802{col 43}-0.3928{col 52}0.694{col 60}-.112982{col 73} .075258
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01886{col 33} .05531{col 43}-0.3410{col 52}0.733{col 60}-.127276{col 73} .089552
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      385{col 34}      535{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.158{col 34}    0.158
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.287{col 34}    0.287
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      272{col 34}      322

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01827{col 33} .03939{col 43}-0.4639{col 52}0.643{col 60}-.095487{col 73} .058937
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01317{col 33} .03939{col 43}-0.3342{col 52}0.738{col 60}-.090377{col 73} .064047
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01317{col 33} .04504{col 43}-0.2923{col 52}0.770{col 60}-.101448{col 73} .075117
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      383{col 34}      531{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.153{col 34}    0.153
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.278{col 34}    0.278
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      272{col 34}      322

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01796{col 33}  .0397{col 43}-0.4524{col 52}0.651{col 60}-.095782{col 73} .059856
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01269{col 33}  .0397{col 43}-0.3195{col 52}0.749{col 60}-.090506{col 73} .065132
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01269{col 33} .04539{col 43}-0.2795{col 52}0.780{col 60}-.101651{col 73} .076278
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      379{col 34}      526{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.148{col 34}    0.148
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.269{col 34}    0.269
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      272{col 34}      322

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01725{col 33} .04002{col 43}-0.4309{col 52}0.667{col 60}-.095684{col 73} .061194
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01176{col 33} .04002{col 43}-0.2939{col 52}0.769{col 60}-.090202{col 73} .066676
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01176{col 33} .04578{col 43}-0.2569{col 52}0.797{col 60}-.101494{col 73} .077968
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      377{col 34}      523{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.143{col 34}    0.143
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.260{col 34}    0.260
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      271{col 34}      321

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01623{col 33} .04037{col 43}-0.4020{col 52}0.688{col 60}-.095356{col 73} .062899
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01035{col 33} .04037{col 43}-0.2564{col 52}0.798{col 60} -.08948{col 73} .068776
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01035{col 33} .04613{col 43}-0.2244{col 52}0.822{col 60}-.100758{col 73} .080054
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      374{col 34}      519{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.251{col 34}    0.251
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      271{col 34}      320

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01521{col 33} .04077{col 43}-0.3730{col 52}0.709{col 60} -.09512{col 73} .064702
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00874{col 33} .04077{col 43}-0.2144{col 52}0.830{col 60}-.088652{col 73} .071171
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00874{col 33} .04651{col 43}-0.1879{col 52}0.851{col 60}-.099905{col 73} .082424
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      370{col 34}      513{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.242{col 34}    0.242
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      271{col 34}      320

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  -.014{col 33} .04125{col 43}-0.3393{col 52}0.734{col 60}-.094853{col 73} .066859
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0071{col 33} .04125{col 43}-0.1721{col 52}0.863{col 60}-.087956{col 73} .073756
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0071{col 33} .04697{col 43}-0.1511{col 52}0.880{col 60}-.099167{col 73} .084967
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      367{col 34}      511{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.128{col 34}    0.128
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.233{col 34}    0.233
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      271{col 34}      320

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01228{col 33} .04179{col 43}-0.2939{col 52}0.769{col 60}-.094198{col 73} .069631
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  -.005{col 33} .04179{col 43}-0.1196{col 52}0.905{col 60}-.086913{col 73} .076916
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  -.005{col 33} .04754{col 43}-0.1052{col 52}0.916{col 60}-.098174{col 73} .088176
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      362{col 34}      504{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.123{col 34}    0.123
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.224{col 34}    0.224
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      271{col 34}      319

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01065{col 33} .04234{col 43}-0.2514{col 52}0.801{col 60}-.093639{col 73} .072348
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00297{col 33} .04234{col 43}-0.0701{col 52}0.944{col 60}-.085962{col 73} .080025
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00297{col 33}  .0481{col 43}-0.0617{col 52}0.951{col 60}-.097245{col 73} .091308
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      355{col 34}      500{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.118{col 34}    0.118
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.215{col 34}    0.215
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      270{col 34}      317

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00996{col 33} .04291{col 43}-0.2321{col 52}0.816{col 60}-.094064{col 73} .074148
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0025{col 33} .04291{col 43}-0.0582{col 52}0.954{col 60}-.086605{col 73} .081607
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0025{col 33} .04867{col 43}-0.0513{col 52}0.959{col 60}-.097898{col 73}   .0929
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      347{col 34}      492{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.113{col 34}    0.113
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.206{col 34}    0.206
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      270{col 34}      317

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01006{col 33} .04349{col 43}-0.2313{col 52}0.817{col 60}  -.0953{col 73} .075177
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00315{col 33} .04349{col 43}-0.0725{col 52}0.942{col 60}-.088391{col 73} .082087
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00315{col 33} .04932{col 43}-0.0639{col 52}0.949{col 60}-.099827{col 73} .093523
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      345{col 34}      486{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.108{col 34}    0.108
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.196{col 34}    0.196
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      269{col 34}      317

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0109{col 33} .04405{col 43}-0.2474{col 52}0.805{col 60}-.097239{col 73} .075444
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00487{col 33} .04405{col 43}-0.1106{col 52}0.912{col 60}-.091212{col 73} .081471
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00487{col 33} .04997{col 43}-0.0975{col 52}0.922{col 60}-.102805{col 73} .093064
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      341{col 34}      476{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.103{col 34}    0.103
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.187{col 34}    0.187
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      266{col 34}      316

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01193{col 33} .04462{col 43}-0.2675{col 52}0.789{col 60}-.099384{col 73} .075516
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00688{col 33} .04462{col 43}-0.1541{col 52}0.878{col 60}-.094326{col 73} .080574
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00688{col 33} .05066{col 43}-0.1357{col 52}0.892{col 60}-.106163{col 73} .092412
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      337{col 34}      468{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.098{col 34}    0.098
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.178{col 34}    0.178
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      263{col 34}      313

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01334{col 33} .04525{col 43}-0.2947{col 52}0.768{col 60}-.102035{col 73} .075361
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00914{col 33} .04525{col 43}-0.2020{col 52}0.840{col 60}-.097842{col 73} .079555
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00914{col 33} .05156{col 43}-0.1773{col 52}0.859{col 60}-.110206{col 73} .091919
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      331{col 34}      458{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.169{col 34}    0.169
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      261{col 34}      312

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01456{col 33} .04591{col 43}-0.3172{col 52}0.751{col 60}-.104538{col 73} .075414
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01129{col 33} .04591{col 43}-0.2460{col 52}0.806{col 60}-.101269{col 73} .078683
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01129{col 33} .05249{col 43}-0.2151{col 52}0.830{col 60} -.11418{col 73} .091595
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      323{col 34}      451{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.088{col 34}    0.088
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.160{col 34}    0.160
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      258{col 34}      308

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01573{col 33} .04655{col 43}-0.3379{col 52}0.735{col 60}-.106976{col 73} .075515
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01298{col 33} .04655{col 43}-0.2789{col 52}0.780{col 60}-.104229{col 73} .078262
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01298{col 33} .05347{col 43}-0.2428{col 52}0.808{col 60}-.117792{col 73} .091825
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      316{col 34}      439{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.083{col 34}    0.083
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.151{col 34}    0.151
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      257{col 34}      306

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01751{col 33}  .0473{col 43}-0.3701{col 52}0.711{col 60}-.110219{col 73} .075204
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01507{col 33}  .0473{col 43}-0.3186{col 52}0.750{col 60} -.10778{col 73} .077643
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01507{col 33} .05451{col 43}-0.2765{col 52}0.782{col 60}  -.1219{col 73} .091763
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      313{col 34}      431{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.142{col 34}    0.142
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      255{col 34}      302

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01991{col 33} .04817{col 43}-0.4134{col 52}0.679{col 60}-.114335{col 73} .074507
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.01959{col 33} .04817{col 43}-0.4066{col 52}0.684{col 60}-.114011{col 73} .074831
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.01959{col 33} .05548{col 43}-0.3531{col 52}0.724{col 60}-.128322{col 73} .089142
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      300{col 34}      414{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.073{col 34}    0.073
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.133{col 34}    0.133
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      251{col 34}      297

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02188{col 33} .04942{col 43}-0.4428{col 52}0.658{col 60}-.118743{col 73}  .07498
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0243{col 33} .04942{col 43}-0.4918{col 52}0.623{col 60}-.121165{col 73} .072557
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0243{col 33} .05681{col 43}-0.4278{col 52}0.669{col 60}-.135652{col 73} .087044
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      288{col 34}      395{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.068{col 34}    0.068
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.124{col 34}    0.124
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      248{col 34}      295

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0253{col 33} .05089{col 43}-0.4971{col 52}0.619{col 60}-.125048{col 73} .074448
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03259{col 33} .05089{col 43}-0.6405{col 52}0.522{col 60}-.132343{col 73} .067153
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03259{col 33} .05845{col 43}-0.5577{col 52}0.577{col 60}-.147151{col 73} .081961
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      275{col 34}      380{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.063{col 34}    0.063
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.115{col 34}    0.115
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      241{col 34}      290

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03082{col 33} .05257{col 43}-0.5863{col 52}0.558{col 60} -.13386{col 73} .072216
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04176{col 33} .05257{col 43}-0.7943{col 52}0.427{col 60}-.144796{col 73}  .06128
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04176{col 33} .06028{col 43}-0.6928{col 52}0.488{col 60}  -.1599{col 73} .076384
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      259{col 34}      361{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.106{col 34}    0.106
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      238{col 34}      284

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0378{col 33} .05432{col 43}-0.6957{col 52}0.487{col 60}-.144267{col 73} .068676
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04995{col 33} .05432{col 43}-0.9195{col 52}0.358{col 60}-.156421{col 73} .056523
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04995{col 33} .06191{col 43}-0.8068{col 52}0.420{col 60}-.171298{col 73}   .0714
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      242{col 34}      340{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.053{col 34}    0.053
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.096{col 34}    0.096
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      234{col 34}      281

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04616{col 33} .05601{col 43}-0.8241{col 52}0.410{col 60}-.155939{col 73} .063624
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05958{col 33} .05601{col 43}-1.0636{col 52}0.287{col 60}-.169357{col 73} .050206
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05958{col 33} .06379{col 43}-0.9340{col 52}0.350{col 60}-.184594{col 73} .065442
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      232{col 34}      321{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.048{col 34}    0.048
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.087{col 34}    0.087
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      230{col 34}      280

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05159{col 33} .05761{col 43}-0.8956{col 52}0.370{col 60}  -.1645{col 73} .061313
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06646{col 33} .05761{col 43}-1.1538{col 52}0.249{col 60} -.17937{col 73} .046442
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06646{col 33} .06556{col 43}-1.0137{col 52}0.311{col 60}-.194968{col 73}  .06204
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      220{col 34}      298{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.043{col 34}    0.043
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.078{col 34}    0.078
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      223{col 34}      273

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0568{col 33} .05958{col 43}-0.9534{col 52}0.340{col 60}-.173573{col 73} .059973
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07285{col 33} .05958{col 43}-1.2228{col 52}0.221{col 60}-.189627{col 73} .043919
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07285{col 33} .06772{col 43}-1.0758{col 52}0.282{col 60}-.205578{col 73}  .05987
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      203{col 34}      275{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.038{col 34}    0.038
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.069{col 34}    0.069
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      215{col 34}      258

Outcome: nfdonate_any15. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06083{col 33} .06246{col 43}-0.9739{col 52}0.330{col 60}-.183252{col 73} .061593
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08084{col 33} .06246{col 43}-1.2943{col 52}0.196{col 60}-.203268{col 73} .041578
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08084{col 33} .07114{col 43}-1.1364{col 52}0.256{col 60}-.220284{col 73} .058594
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}{txt}number of observations will be reset to 26
Press any key to continue, or Break to abort
{p}
Number of observations ({bf:_N}) was 0,
now 26.
{p_end}
{res}{txt}{p 0 4 2}
file {bf}
Fig_H5_nfdonate_any15.pdf{rm}
saved as
PDF
format
{p_end}
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      260{col 34}      361{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.058{col 34}    0.058
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.106{col 34}    0.106
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      238{col 34}      284

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05351{col 33} .04754{col 43}-1.1258{col 52}0.260{col 60}-.146684{col 73} .039655
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06438{col 33} .04754{col 43}-1.3544{col 52}0.176{col 60}-.157554{col 73} .028785
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06438{col 33} .05375{col 43}-1.1979{col 52}0.231{col 60}-.169726{col 73} .040957
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      353{col 34}      496{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.116{col 34}    0.116
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.211{col 34}    0.211
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      270{col 34}      317

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02537{col 33} .03788{col 43}-0.6698{col 52}0.503{col 60} -.09962{col 73} .048873
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02256{col 33} .03788{col 43}-0.5957{col 52}0.551{col 60}-.096811{col 73} .051682
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02256{col 33} .04294{col 43}-0.5255{col 52}0.599{col 60}-.106726{col 73} .061597
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      346{col 34}      490{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.202{col 34}    0.202
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      269{col 34}      317

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02576{col 33} .03846{col 43}-0.6698{col 52}0.503{col 60} -.10114{col 73} .049619
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02352{col 33} .03846{col 43}-0.6116{col 52}0.541{col 60}-.098902{col 73} .051857
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02352{col 33}  .0436{col 43}-0.5395{col 52}0.590{col 60}-.108973{col 73} .061928
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      344{col 34}      481{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.106{col 34}    0.106
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.193{col 34}    0.193
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      267{col 34}      316

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} -.0261{col 33} .03902{col 43}-0.6690{col 52}0.504{col 60}-.102576{col 73} .050373
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02457{col 33} .03902{col 43}-0.6297{col 52}0.529{col 60}-.101045{col 73} .051904
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02457{col 33} .04423{col 43}-0.5555{col 52}0.579{col 60}-.111263{col 73} .062121
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      340{col 34}      473{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.101{col 34}    0.101
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.184{col 34}    0.184
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      266{col 34}      316

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02664{col 33} .03958{col 43}-0.6729{col 52}0.501{col 60}-.104222{col 73} .050946
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02608{col 33} .03958{col 43}-0.6589{col 52}0.510{col 60}-.103667{col 73} .051501
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02608{col 33} .04497{col 43}-0.5800{col 52}0.562{col 60}-.114224{col 73} .062058
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      334{col 34}      464{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.096{col 34}    0.096
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.175{col 34}    0.175
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      263{col 34}      312

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02746{col 33}  .0402{col 43}-0.6830{col 52}0.495{col 60}-.106244{col 73} .051331
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02794{col 33}  .0402{col 43}-0.6952{col 52}0.487{col 60}-.106732{col 73} .050843
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02794{col 33} .04581{col 43}-0.6100{col 52}0.542{col 60}-.117731{col 73} .061842
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      326{col 34}      454{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.091{col 34}    0.091
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.165{col 34}    0.165
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      260{col 34}      311

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02898{col 33} .04077{col 43}-0.7109{col 52}0.477{col 60}-.108888{col 73} .050925
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03011{col 33} .04077{col 43}-0.7385{col 52}0.460{col 60}-.110014{col 73} .049798
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03011{col 33} .04656{col 43}-0.6467{col 52}0.518{col 60}-.121361{col 73} .061145
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      322{col 34}      447{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.086{col 34}    0.086
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.156{col 34}    0.156
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      258{col 34}      307

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03058{col 33}  .0414{col 43}-0.7386{col 52}0.460{col 60}-.111726{col 73} .050565
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03238{col 33}  .0414{col 43}-0.7821{col 52}0.434{col 60}-.113525{col 73} .048766
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03238{col 33} .04738{col 43}-0.6834{col 52}0.494{col 60}-.125248{col 73} .060489
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      314{col 34}      435{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.081{col 34}    0.081
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.147{col 34}    0.147
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      257{col 34}      306

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03321{col 33} .04211{col 43}-0.7886{col 52}0.430{col 60}-.115735{col 73}  .04932
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03588{col 33} .04211{col 43}-0.8521{col 52}0.394{col 60}-.118408{col 73} .046647
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03588{col 33}  .0482{col 43}-0.7444{col 52}0.457{col 60}-.130347{col 73} .058587
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      308{col 34}      425{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.076{col 34}    0.076
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.138{col 34}    0.138
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      252{col 34}      300

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03548{col 33} .04301{col 43}-0.8250{col 52}0.409{col 60}-.119771{col 73} .048812
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03985{col 33} .04301{col 43}-0.9266{col 52}0.354{col 60} -.12414{col 73} .044443
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03985{col 33} .04907{col 43}-0.8122{col 52}0.417{col 60}-.136015{col 73} .056318
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      296{col 34}      409{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.071{col 34}    0.071
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.129{col 34}    0.129
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      250{col 34}      296

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03788{col 33}  .0441{col 43}-0.8591{col 52}0.390{col 60}-.124313{col 73} .048547
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04439{col 33}  .0441{col 43}-1.0066{col 52}0.314{col 60}-.130819{col 73} .042041
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04439{col 33} .05024{col 43}-0.8835{col 52}0.377{col 60}-.142857{col 73}  .05408
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      284{col 34}      390{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.066{col 34}    0.066
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.120{col 34}    0.120
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      246{col 34}      293

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}  -.043{col 33} .04537{col 43}-0.9479{col 52}0.343{col 60}-.131925{col 73} .045916
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05175{col 33} .04537{col 43}-1.1406{col 52}0.254{col 60}-.140667{col 73} .037175
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05175{col 33} .05164{col 43}-1.0020{col 52}0.316{col 60}-.152967{col 73} .049476
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      266{col 34}      370{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.061{col 34}    0.061
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.111{col 34}    0.111
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      239{col 34}      287

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04965{col 33} .04676{col 43}-1.0617{col 52}0.288{col 60}-.141305{col 73} .042004
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.05972{col 33} .04676{col 43}-1.2770{col 52}0.202{col 60}-.151372{col 73} .031937
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.05972{col 33}   .053{col 43}-1.1267{col 52}0.260{col 60}-.163603{col 73} .044168
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      253{col 34}      352{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.102{col 34}    0.102
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      237{col 34}      283

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05646{col 33}  .0483{col 43}-1.1688{col 52}0.242{col 60}-.151133{col 73} .038218
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06817{col 33}  .0483{col 43}-1.4112{col 52}0.158{col 60}-.162842{col 73} .026509
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06817{col 33} .05454{col 43}-1.2498{col 52}0.211{col 60}-.175067{col 73} .038734
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      239{col 34}      333{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.051{col 34}    0.051
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.093{col 34}    0.093
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      233{col 34}      281

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05995{col 33} .04964{col 43}-1.2076{col 52}0.227{col 60}-.157253{col 73}  .03735
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07379{col 33} .04964{col 43}-1.4864{col 52}0.137{col 60}-.171094{col 73}  .02351
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07379{col 33} .05625{col 43}-1.3120{col 52}0.190{col 60}-.184031{col 73} .036448
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      231{col 34}      315{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.046{col 34}    0.046
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.084{col 34}    0.084
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      226{col 34}      277

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06268{col 33} .05115{col 43}-1.2255{col 52}0.220{col 60}-.162938{col 73} .037568
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.07714{col 33} .05115{col 43}-1.5081{col 52}0.132{col 60}-.177391{col 73} .023115
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.07714{col 33} .05801{col 43}-1.3297{col 52}0.184{col 60}-.190837{col 73} .036561
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      218{col 34}      294{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.041{col 34}    0.041
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.075{col 34}    0.075
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      220{col 34}      268

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06618{col 33} .05315{col 43}-1.2450{col 52}0.213{col 60}-.170359{col 73} .038004
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08162{col 33} .05315{col 43}-1.5356{col 52}0.125{col 60}-.185805{col 73} .022557
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08162{col 33} .06041{col 43}-1.3512{col 52}0.177{col 60}-.200019{col 73} .036771
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      194{col 34}      260{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.036{col 34}    0.036
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.065{col 34}    0.065
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      207{col 34}      248

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.06777{col 33} .05618{col 43}-1.2063{col 52}0.228{col 60}-.177877{col 73} .042337
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08356{col 33} .05618{col 43}-1.4875{col 52}0.137{col 60}-.193671{col 73} .026543
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08356{col 33}  .0642{col 43}-1.3017{col 52}0.193{col 60}-.209384{col 73} .042257
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      178{col 34}      241{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.031{col 34}    0.031
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.056{col 34}    0.056
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      192{col 34}      231

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07711{col 33} .06064{col 43}-1.2716{col 52}0.204{col 60}-.195956{col 73} .041743
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.08737{col 33} .06064{col 43}-1.4408{col 52}0.150{col 60}-.206219{col 73} .031481
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.08737{col 33} .07049{col 43}-1.2395{col 52}0.215{col 60}-.225523{col 73} .050785
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1007
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:Manual}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      425{col 34}      582{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      149{col 34}      208{col 55}{txt}VCE method    = {res}{ralign 10:Cluster}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}    0.026{col 34}    0.026
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}    0.047{col 34}    0.047
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.550{col 34}    0.550
{txt}{ralign 18:Number of clusters}{col 19} {c |} {col 21}{res}      180{col 34}      217

Outcome: nfb5. Running variable: rv2.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.09698{col 33} .06677{col 43}-1.4525{col 52}0.146{col 60}-.227854{col 73} .033885
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.10859{col 33} .06677{col 43}-1.6262{col 52}0.104{col 60}-.239455{col 73} .022284
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.10859{col 33} .07775{col 43}-1.3966{col 52}0.163{col 60}-.260972{col 73} .043801
{txt}{hline 19}{c BT}{hline 60}
Std. Err. adjusted for clusters in muni_code
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